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Healthcare (Basel, Switzerland) Feb 2021Blockchain technology was introduced through Bitcoin in a 2008 whitepaper by the mysterious Satoshi Nakamoto. Since its inception, it has gathered great attention... (Review)
Review
Blockchain technology was introduced through Bitcoin in a 2008 whitepaper by the mysterious Satoshi Nakamoto. Since its inception, it has gathered great attention because of its unique properties-immutability and decentralized authority. This technology is now being implemented in various fields such as healthcare, IoT, data management, etc., apart from cryptocurrencies. As it is a newly emerging technology, researchers and organizations face many challenges in integrating this technology into other fields. Consent management is one of the essential processes in an organization because of the ever-evolving privacy laws, which are introduced to provide more control to users over their data. This paper is a systematic review of Blockchain's application in the field of consent and privacy data management. The review discusses the adaptation of Blockchain in healthcare, IoT, identity management, and data storage. This analysis is formed on the principles of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) and a process of systematic mapping review. We provide analysis of the development, challenges, and limitations of blockchain technology for consent management.
PubMed: 33535465
DOI: 10.3390/healthcare9020137 -
Multimedia Tools and Applications Feb 2023In today's world, health and medicine play an undeniable role in human life. Traditional and current Electronic Health Records (EHR) systems that are used to exchange...
In today's world, health and medicine play an undeniable role in human life. Traditional and current Electronic Health Records (EHR) systems that are used to exchange information between medical stakeholders (patients, physicians, insurance companies, pharmaceuticals, medical researchers, etc.) suffer weaknesses in terms of security and privacy due to having centralized architecture. Blockchain technology ensures the privacy and security of EHR systems thanks to the use of encryption. Moreover, due to its decentralized nature, this technology prevents central failure and central attack points. In this paper, a systematic literature review (SLR) is proposed to analyze the existing Blockchain-based approaches for improving privacy and security in electronic health systems. The research methodology, paper selection process, and the search query are explained. 51 papers returned from our search criteria published between 2018 and Dec 2022 are reviewed. The main ideas, type of Blockchain, evaluation metrics, and used tools of each selected paper are discussed in detail. Finally, future research directions, open challenges, and some issues are discussed.
PubMed: 36811000
DOI: 10.1007/s11042-023-14488-w -
JMIR MHealth and UHealth Apr 2022Loneliness and social isolation are associated with multiple health problems, including depression, functional impairment, and death. Mobile sensing using smartphones... (Review)
Review
BACKGROUND
Loneliness and social isolation are associated with multiple health problems, including depression, functional impairment, and death. Mobile sensing using smartphones and wearable devices, such as fitness trackers or smartwatches, as well as ambient sensors, can be used to acquire data remotely on individuals and their daily routines and behaviors in real time. This has opened new possibilities for the early detection of health and social problems, including loneliness and social isolation.
OBJECTIVE
This scoping review aimed to identify and synthesize recent scientific studies that used passive sensing techniques, such as the use of in-home ambient sensors, smartphones, and wearable device sensors, to collect data on device users' daily routines and behaviors to detect loneliness or social isolation. This review also aimed to examine various aspects of these studies, especially target populations, privacy, and validation issues.
METHODS
A scoping review was undertaken, following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). Studies on the topic under investigation were identified through 6 databases (IEEE Xplore, Scopus, ACM, PubMed, Web of Science, and Embase). The identified studies were screened for the type of passive sensing detection methods for loneliness and social isolation, targeted population, reliability of the detection systems, challenges, and limitations of these detection systems.
RESULTS
After conducting the initial search, a total of 40,071 papers were identified. After screening for inclusion and exclusion criteria, 29 (0.07%) studies were included in this scoping review. Most studies (20/29, 69%) used smartphone and wearable technology to detect loneliness or social isolation, and 72% (21/29) of the studies used a validated reference standard to assess the accuracy of passively collected data for detecting loneliness or social isolation.
CONCLUSIONS
Despite the growing use of passive sensing technologies for detecting loneliness and social isolation, some substantial gaps still remain in this domain. A population heterogeneity issue exists among several studies, indicating that different demographic characteristics, such as age and differences in participants' behaviors, can affect loneliness and social isolation. In addition, despite extensive personal data collection, relatively few studies have addressed privacy and ethical issues. This review provides uncertain evidence regarding the use of passive sensing to detect loneliness and social isolation. Future research is needed using robust study designs, measures, and examinations of privacy and ethical concerns.
Topics: Humans; Loneliness; Reproducibility of Results; Smartphone; Social Isolation; Wearable Electronic Devices
PubMed: 35412465
DOI: 10.2196/34638 -
Medicine Aug 2018Published studies have reported conflicting and heterogeneous results regarding the association between human leukocyte antigen (HLA)-DRB1 polymorphisms and alopecia... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Published studies have reported conflicting and heterogeneous results regarding the association between human leukocyte antigen (HLA)-DRB1 polymorphisms and alopecia areata (AA). This study aimed to review and quantitatively analyze the association between HLA-DRB1 polymorphisms and AA.
METHODS
In this study, all relevant publications were searched through December 2016. Odds ratios (ORs) and confidence intervals (CIs) for comparisons between case and control groups were calculated. Stata 14.0 software was used to perform statistical analysis. This research does not require formal ethical approval because the data used in this analysis do not involve personal information and thus do not affect privacy.
RESULTS
Twelve articles were identified. For HLA-DRB1*04 and HLA-DRB1*16 polymorphisms, the OR (95% CIs) was 1.49 (1.24-1.78) and 1.61 (1.08-2.41), and P was <.01 and <.01, respectively. For HLA-DRB1*0301, HLA-DRB1*09, and HLA-DRB1*13 polymorphisms, the OR (95% CIs) was 0.42 (0.28-0.63), 0.74 (0.55-0.99), and 0.62 (0.40-0.98), and P was <.01, <.01, and <.01, respectively. Statistical evidence revealed no publication bias (P > .05).
CONCLUSION
The present meta-analysis suggested that HLA-DRB1*04 and HLA-DRB1*16 polymorphisms might be associated with increased AA risk, while HLA-DRB1*0301, HLA-DRB1*09, and HLA-DRB1*13 polymorphisms might decrease the AA risk. Studies with adequate methodological quality on gene-gene and gene-environment interactions are needed to validate the results in the future.
Topics: Alleles; Alopecia Areata; Case-Control Studies; Genetic Predisposition to Disease; HLA-DRB1 Chains; Humans; Odds Ratio; Polymorphism, Single Nucleotide
PubMed: 30095639
DOI: 10.1097/MD.0000000000011790 -
Journal of Medical Internet Research May 2024Mobile health (mHealth) apps have the potential to enhance health care service delivery. However, concerns regarding patients' confidentiality, privacy, and security... (Review)
Review
BACKGROUND
Mobile health (mHealth) apps have the potential to enhance health care service delivery. However, concerns regarding patients' confidentiality, privacy, and security consistently affect the adoption of mHealth apps. Despite this, no review has comprehensively summarized the findings of studies on this subject matter.
OBJECTIVE
This systematic review aims to investigate patients' perspectives and awareness of the confidentiality, privacy, and security of the data collected through mHealth apps.
METHODS
Using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, a comprehensive literature search was conducted in 3 electronic databases: PubMed, Ovid, and ScienceDirect. All the retrieved articles were screened according to specific inclusion criteria to select relevant articles published between 2014 and 2022.
RESULTS
A total of 33 articles exploring mHealth patients' perspectives and awareness of data privacy, security, and confidentiality issues and the associated factors were included in this systematic review. Thematic analyses of the retrieved data led to the synthesis of 4 themes: concerns about data privacy, confidentiality, and security; awareness; facilitators and enablers; and associated factors. Patients showed discordant and concordant perspectives regarding data privacy, security, and confidentiality, as well as suggesting approaches to improve the use of mHealth apps (facilitators), such as protection of personal data, ensuring that health status or medical conditions are not mentioned, brief training or education on data security, and assuring data confidentiality and privacy. Similarly, awareness of the subject matter differed across the studies, suggesting the need to improve patients' awareness of data security and privacy. Older patients, those with a history of experiencing data breaches, and those belonging to the higher-income class were more likely to raise concerns about the data security and privacy of mHealth apps. These concerns were not frequent among patients with higher satisfaction levels and those who perceived the data type to be less sensitive.
CONCLUSIONS
Patients expressed diverse views on mHealth apps' privacy, security, and confidentiality, with some of the issues raised affecting technology use. These findings may assist mHealth app developers and other stakeholders in improving patients' awareness and adjusting current privacy and security features in mHealth apps to enhance their adoption and use.
TRIAL REGISTRATION
PROSPERO CRD42023456658; https://tinyurl.com/ytnjtmca.
Topics: Humans; Confidentiality; Telemedicine; Mobile Applications; Computer Security; Privacy
PubMed: 38820572
DOI: 10.2196/50715 -
Journal of Dentistry Jul 2022This scoping review aims to review explore, assess, and map the literature to inform clinical practice regarding communication between clinicians. Specific Apps/channels... (Review)
Review
OBJECTIVES
This scoping review aims to review explore, assess, and map the literature to inform clinical practice regarding communication between clinicians. Specific Apps/channels used were identified and assessed with a focus on data security with key concepts and knowledge gaps identified.
DATA
The Joanna Briggs Institute framework is followed, with search results reported as per the PRISMA ScR for scoping reviews guidelines.
SOURCES
A systematic search strategy encompassing EBSCO and OneSearch databases was conducted - two identical searches, (June and October 2020) limited to English language articles published 2016-2020. A narrative synthesis was used to integrate and report the findings.
STUDY SELECTION
Sixty-six publications were selected. Twelve from EBSCO, thirty-five from OneSearch, nineteen were hand searched. Sixteen of the publications were research studies, nine were literature reviews, twenty-six were editorial, one was a newspaper article and fourteen were grey literature. Instant Messaging (40%, n = 23), image sharing (41%, n = 24), and video conferencing (19%, n = 11) were functions most popular with clinicians. WhatsApp, generic instant messaging, Facebook messenger, ZOOM, and Skype are evidenced as channels for communication between clinicians within the EU. A sizeable proportion of the publications (38%; n = 25) failed to identify or adequately address technical security concerns and requirements around privacy and data protection.
CONCLUSIONS
Clinicians use smartphones /Apps to communicate clinical information with each other. The security and privacy issues arising from their communication of sensitive data is absent or only superficially acknowledged within the literature.
CLINICAL SIGNIFICANCE
Clinician's need clearer guidance on the use of smartphone technology for clinical communications.
Topics: Communication; Computer Security; Humans; Privacy; Smartphone; Technology
PubMed: 35413411
DOI: 10.1016/j.jdent.2022.104112 -
The Cochrane Database of Systematic... May 2021Social networking platforms offer a wide reach for public health interventions allowing communication with broad audiences using tools that are generally free and... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Social networking platforms offer a wide reach for public health interventions allowing communication with broad audiences using tools that are generally free and straightforward to use and may be combined with other components, such as public health policies. We define interactive social media as activities, practices, or behaviours among communities of people who have gathered online to interactively share information, knowledge, and opinions.
OBJECTIVES
We aimed to assess the effectiveness of interactive social media interventions, in which adults are able to communicate directly with each other, on changing health behaviours, body functions, psychological health, well-being, and adverse effects. Our secondary objective was to assess the effects of these interventions on the health of populations who experience health inequity as defined by PROGRESS-Plus. We assessed whether there is evidence about PROGRESS-Plus populations being included in studies and whether results are analysed across any of these characteristics.
SEARCH METHODS
We searched CENTRAL, CINAHL, Embase, MEDLINE (including trial registries) and PsycINFO. We used Google, Web of Science, and relevant web sites to identify additional studies and searched reference lists of included studies. We searched for published and unpublished studies from 2001 until June 1, 2020. We did not limit results by language.
SELECTION CRITERIA
We included randomised controlled trials (RCTs), controlled before-and-after (CBAs) and interrupted time series studies (ITSs). We included studies in which the intervention website, app, or social media platform described a goal of changing a health behaviour, or included a behaviour change technique. The social media intervention had to be delivered to adults via a commonly-used social media platform or one that mimicked a commonly-used platform. We included studies comparing an interactive social media intervention alone or as a component of a multi-component intervention with either a non-interactive social media control or an active but less-interactive social media comparator (e.g. a moderated versus an unmoderated discussion group). Our main outcomes were health behaviours (e.g. physical activity), body function outcomes (e.g. blood glucose), psychological health outcomes (e.g. depression), well-being, and adverse events. Our secondary outcomes were process outcomes important for behaviour change and included knowledge, attitudes, intention and motivation, perceived susceptibility, self-efficacy, and social support.
DATA COLLECTION AND ANALYSIS
We used a pre-tested data extraction form and collected data independently, in duplicate. Because we aimed to assess broad outcomes, we extracted only one outcome per main and secondary outcome categories prioritised by those that were the primary outcome as reported by the study authors, used in a sample size calculation, and patient-important.
MAIN RESULTS
We included 88 studies (871,378 participants), of which 84 were RCTs, three were CBAs and one was an ITS. The majority of the studies were conducted in the USA (54%). In total, 86% were conducted in high-income countries and the remaining 14% in upper middle-income countries. The most commonly used social media platform was Facebook (39%) with few studies utilising other platforms such as WeChat, Twitter, WhatsApp, and Google Hangouts. Many studies (48%) used web-based communities or apps that mimic functions of these well-known social media platforms. We compared studies assessing interactive social media interventions with non-interactive social media interventions, which included paper-based or in-person interventions or no intervention. We only reported the RCT results in our 'Summary of findings' table. We found a range of effects on health behaviours, such as breastfeeding, condom use, diet quality, medication adherence, medical screening and testing, physical activity, tobacco use, and vaccination. For example, these interventions may increase physical activity and medical screening tests but there was little to no effect for other health behaviours, such as improved diet or reduced tobacco use (20,139 participants in 54 RCTs). For body function outcomes, interactive social media interventions may result in small but important positive effects, such as a small but important positive effect on weight loss and a small but important reduction in resting heart rate (4521 participants in 30 RCTs). Interactive social media may improve overall well-being (standardised mean difference (SMD) 0.46, 95% confidence interval (CI) 0.14 to 0.79, moderate effect, low-certainty evidence) demonstrated by an increase of 3.77 points on a general well-being scale (from 1.15 to 6.48 points higher) where scores range from 14 to 70 (3792 participants in 16 studies). We found no difference in effect on psychological outcomes (depression and distress) representing a difference of 0.1 points on a standard scale in which scores range from 0 to 63 points (SMD -0.01, 95% CI -0.14 to 0.12, low-certainty evidence, 2070 participants in 12 RCTs). We also compared studies assessing interactive social media interventions with those with an active but less interactive social media control (11 studies). Four RCTs (1523 participants) that reported on physical activity found an improvement demonstrated by an increase of 28 minutes of moderate-to-vigorous physical activity per week (from 10 to 47 minutes more, SMD 0.35, 95% CI 0.12 to 0.59, small effect, very low-certainty evidence). Two studies found little to no difference in well-being for those in the intervention and control groups (SMD 0.02, 95% CI -0.08 to 0.13, small effect, low-certainty evidence), demonstrated by a mean change of 0.4 points on a scale with a range of 0 to 100. Adverse events related to the social media component of the interventions, such as privacy issues, were not reported in any of our included studies. We were unable to conduct planned subgroup analyses related to health equity as only four studies reported relevant data.
AUTHORS' CONCLUSIONS
This review combined data for a variety of outcomes and found that social media interventions that aim to increase physical activity may be effective and social media interventions may improve well-being. While we assessed many other outcomes, there were too few studies to compare or, where there were studies, the evidence was uncertain. None of our included studies reported adverse effects related to the social media component of the intervention. Future studies should assess adverse events related to the interactive social media component and should report on population characteristics to increase our understanding of the potential effect of these interventions on reducing health inequities.
Topics: Adolescent; Adult; Behavior Therapy; Bias; Controlled Before-After Studies; Exercise; Fruit; Health Behavior; Health Equity; Heart Rate; Humans; Interrupted Time Series Analysis; Randomized Controlled Trials as Topic; Social Media; Social Networking; Treatment Outcome; Vegetables; Weight Loss; Young Adult
PubMed: 34057201
DOI: 10.1002/14651858.CD012932.pub2 -
Journal of Medical Internet Research Jul 2021Functionalities of personal health record (PHR) are evolving, and continued discussions about PHR functionalities need to be performed to keep it up-to-date.... (Review)
Review
BACKGROUND
Functionalities of personal health record (PHR) are evolving, and continued discussions about PHR functionalities need to be performed to keep it up-to-date. Technological issues such as nonfunctional requirements should also be discussed in the implementation of PHR.
OBJECTIVE
This study systematically reviewed the main functionalities and issues in implementing the PHR.
METHODS
This systematic review was conducted using Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The search is performed using the online databases Scopus, ScienceDirect, IEEE, MEDLINE, CINAHL, and PubMed for English journal articles and conference proceedings published between 2015 and 2020.
RESULTS
A total of 105 articles were selected in the review. Seven function categories were identified in this review, which is grouped into basic and advanced functions. Health records and administrative records were grouped into basic functions. Medication management, communication, appointment management, education, and self-health monitoring were grouped into advanced functions. The issues found in this study include interoperability, security and privacy, usability, data quality, and personalization.
CONCLUSIONS
In addition to PHR basic and advanced functions, other supporting functionalities may also need to be developed based on the issues identified in this study. This paper provides an integrated PHR architectural model that describes the functional requirements and data sources of PHRs.
Topics: Health Records, Personal; Humans; Information Storage and Retrieval; Medical Records Systems, Computerized; Technology
PubMed: 34287210
DOI: 10.2196/26236 -
Annals of Internal Medicine Jan 2024Severe maternal morbidity and mortality are worse in the United States than in all similar countries, with the greatest effect on Black women. Emerging research suggests... (Review)
Review
BACKGROUND
Severe maternal morbidity and mortality are worse in the United States than in all similar countries, with the greatest effect on Black women. Emerging research suggests that disrespectful care during childbirth contributes to this problem.
PURPOSE
To conduct a systematic review on definitions and valid measurements of respectful maternity care (RMC), its effectiveness for improving maternal and infant health outcomes for those who are pregnant and postpartum, and strategies for implementation.
DATA SOURCES
Systematic searches of Ovid Medline, CINAHL, Embase, Cochrane Central Register of Controlled Trials, PsycInfo, and SocINDEX for English-language studies (inception to July 2023).
STUDY SELECTION
Randomized controlled trials and nonrandomized studies of interventions of RMC versus usual care for effectiveness studies; additional qualitative and noncomparative validation studies for definitions and measurement studies.
DATA EXTRACTION
Dual data abstraction and quality assessment using established methods, with resolution of disagreements through consensus.
DATA SYNTHESIS
Thirty-seven studies were included across all questions, of which 1 provided insufficient evidence on the effectiveness of RMC to improve maternal outcomes and none studied RMC to improve infant outcomes. To define RMC, authors identified 12 RMC frameworks, from which 2 main concepts were identified: and frameworks. Disrespect and abuse components focused on recognizing birth mistreatment; rights-based frameworks incorporated aspects of reproductive justice, human rights, and antiracism. Five overlapping framework themes include freedom from abuse, consent, privacy, dignity, communication, safety, and justice. Twelve tools to measure RMC were validated in 24 studies on content validity, construct validity, and internal consistency, but lack of a gold standard limited evaluation of criterion validity. Three tools specific for RMC had at least 1 study demonstrating consistency internally and with an intended construct relevant to U.S. settings, but no single tool stands out as the best measure of RMC.
LIMITATIONS
No studies evaluated other health outcomes or RMC implementation strategies. The lack of definition and gold standard limit evaluation of RMC tools.
CONCLUSION
Frameworks for RMC are well described but vary in their definitions. Tools to measure RMC demonstrate consistency but lack a gold standard, requiring further evaluation before implementation in U.S. settings. Evidence is lacking on the effectiveness of implementing RMC to improve any maternal or infant health outcome.
PRIMARY FUNDING SOURCE
Agency for Healthcare Research and Quality. (PROSPERO: CRD42023394769).
Topics: Infant; Pregnancy; Female; Humans; Maternal Health Services; Respect; Obstetrics; Delivery, Obstetric; Postpartum Period; Quality of Health Care
PubMed: 38163377
DOI: 10.7326/M23-2676 -
Perspectives in Health Information... 2023The objective of the study is to identify challenges and associated factors for privacy and security related to telehealth visits during the COVID-19 pandemic. The...
The objective of the study is to identify challenges and associated factors for privacy and security related to telehealth visits during the COVID-19 pandemic. The systematic search strategy used the databases of PubMed, ScienceDirect, ProQuest, Embase, CINAHL, and COCHRANE, with the search terms of telehealth/telemedicine, privacy, security, and confidentiality. Reviews included peer-reviewed empirical studies conducted from January 2020 to February 2022. Studies conducted outside of the US, non-empirical, and non-telehealth related were excluded. Eighteen studies were included in the final analysis. Three risk factors associated with privacy and security in telehealth practice included: environmental factors (lack of private space for vulnerable populations, difficulty sharing sensitive health information remotely), technology factors (data security issues, limited access to the internet, and technology), and operational factors (reimbursement, payer denials, technology accessibility, training, and education). Findings from this study can assist governments, policymakers, and healthcare organizations in developing best practices in telehealth privacy and security strategies.
Topics: Humans; Privacy; Pandemics; COVID-19; Confidentiality; Risk Factors; Telemedicine
PubMed: 37215337
DOI: No ID Found