-
Journal of Clinical Nursing Jul 2023Artificial Intelligence (AI) techniques are being applied in nursing and midwifery to improve decision-making, patient care and service delivery. However, an... (Review)
Review
BACKGROUND
Artificial Intelligence (AI) techniques are being applied in nursing and midwifery to improve decision-making, patient care and service delivery. However, an understanding of the real-world applications of AI across all domains of both professions is limited.
OBJECTIVES
To synthesise literature on AI in nursing and midwifery.
METHODS
CINAHL, Embase, PubMed and Scopus were searched using relevant terms. Titles, abstracts and full texts were screened against eligibility criteria. Data were extracted, analysed, and findings were presented in a descriptive summary. The PRISMA checklist guided the review conduct and reporting.
RESULTS
One hundred and forty articles were included. Nurses' and midwives' involvement in AI varied, with some taking an active role in testing, using or evaluating AI-based technologies; however, many studies did not include either profession. AI was mainly applied in clinical practice to direct patient care (n = 115, 82.14%), with fewer studies focusing on administration and management (n = 21, 15.00%), or education (n = 4, 2.85%). Benefits reported were primarily potential as most studies trained and tested AI algorithms. Only a handful (n = 8, 7.14%) reported actual benefits when AI techniques were applied in real-world settings. Risks and limitations included poor quality datasets that could introduce bias, the need for clinical interpretation of AI-based results, privacy and trust issues, and inadequate AI expertise among the professions.
CONCLUSION
Digital health datasets should be put in place to support the testing, use, and evaluation of AI in nursing and midwifery. Curricula need to be developed to educate the professions about AI, so they can lead and participate in these digital initiatives in healthcare.
RELEVANCE FOR CLINICAL PRACTICE
Adult, paediatric, mental health and learning disability nurses, along with midwives should have a more active role in rigorous, interdisciplinary research evaluating AI-based technologies in professional practice to determine their clinical efficacy as well as their ethical, legal and social implications in healthcare.
Topics: Pregnancy; Adult; Humans; Child; Female; Midwifery; Artificial Intelligence; Delivery of Health Care; Curriculum
PubMed: 35908207
DOI: 10.1111/jocn.16478 -
Cureus Aug 2023Adolescents increasingly find it difficult to picture their lives without social media. Practitioners need to be able to assess risk, and social media may be a new... (Review)
Review
Adolescents increasingly find it difficult to picture their lives without social media. Practitioners need to be able to assess risk, and social media may be a new component to consider. Although there is limited empirical evidence to support the claim, the perception of the link between social media and mental health is heavily influenced by teenage and professional perspectives. Privacy concerns, cyberbullying, and bad effects on schooling and mental health are all risks associated with this population's usage of social media. However, ethical social media use can expand opportunities for connection and conversation, as well as boost self-esteem, promote health, and gain access to critical medical information. Despite mounting evidence of social media's negative effects on adolescent mental health, there is still a scarcity of empirical research on how teens comprehend social media, particularly as a body of wisdom, or how they might employ wider modern media discourses to express themselves. Youth use cell phones and other forms of media in large numbers, resulting in chronic sleep loss, which has a negative influence on cognitive ability, school performance, and socio-emotional functioning. According to data from several cross-sectional, longitudinal, and empirical research, smartphone and social media use among teenagers relates to an increase in mental distress, self-harming behaviors, and suicidality. Clinicians can work with young people and their families to reduce the hazards of social media and smartphone usage by using open, nonjudgmental, and developmentally appropriate tactics, including education and practical problem-solving.
PubMed: 37671234
DOI: 10.7759/cureus.42990 -
Journal of Clinical Oncology : Official... Oct 2023Adjuvant endocrine therapy (AET) adherence among breast cancer survivors is often suboptimal, leading to higher cancer recurrence and mortality. Intervention studies to... (Meta-Analysis)
Meta-Analysis Review
PURPOSE
Adjuvant endocrine therapy (AET) adherence among breast cancer survivors is often suboptimal, leading to higher cancer recurrence and mortality. Intervention studies to promote AET adherence have burgeoned, more than doubling in number since this literature was last reviewed. The current aim is to provide an up-to-date systematic review and meta-analysis of interventions to enhance AET adherence and to identify strengths and limitations of existing interventions to inform future research and clinical care.
METHODS
Systematic searches were conducted in three electronic databases. Studies were included in the systematic review if they examined an intervention for promoting AET adherence among breast cancer survivors. Studies were further included in the meta-analyses if they examined a measure of AET adherence (defined as compliance or persistence beyond initiation) and reported (or provided upon request) sufficient information to calculate an effect size.
RESULTS
Of 5,045 unique records, 33 unique studies representing 375,951 women met inclusion criteria for the systematic review. Interventions that educated patients about how to manage side effects generally failed to improve AET adherence, whereas policy changes that lowered AET costs consistently improved adherence. Medication reminders, communication, and psychological/coping strategies showed varied efficacy. Of the 33 studies that met the inclusion criteria for the systematic review, 25 studies representing 367,873 women met inclusion criteria for the meta-analysis. The meta-analysis showed statistically significant effects of the adherence interventions overall relative to study-specified control conditions (number of studies [k] = 25; odds ratio, 1.412; 95% CI, 1.183 to 1.682; = .0001). Subgroup analyses showed that there were no statistically significant differences in effect sizes by study design (randomized controlled trial other), publication year, directionality of the intervention (unidirectional bidirectional contact), or intervention type.
CONCLUSION
To our knowledge, this is the first known meta-analysis to demonstrate a significant effect for interventions to promote AET adherence. The systematic review revealed that lowering medication costs and a subgroup of psychosocial and reminder interventions showed the most promise, informing future research, policy, and clinical directions.
Topics: Humans; Female; Breast Neoplasms; Cancer Survivors; Medication Adherence; Chemotherapy, Adjuvant; Adaptation, Psychological
PubMed: 37531593
DOI: 10.1200/JCO.23.00697 -
Neural Networks : the Official Journal... Jun 2024Unsupervised domain adaptation (UDA) via deep learning has attracted appealing attention for tackling domain-shift problems caused by distribution discrepancy across... (Review)
Review
Unsupervised domain adaptation (UDA) via deep learning has attracted appealing attention for tackling domain-shift problems caused by distribution discrepancy across different domains. Existing UDA approaches highly depend on the accessibility of source domain data, which is usually limited in practical scenarios due to privacy protection, data storage and transmission cost, and computation burden. To tackle this issue, many source-free unsupervised domain adaptation (SFUDA) methods have been proposed recently, which perform knowledge transfer from a pre-trained source model to the unlabeled target domain with source data inaccessible. A comprehensive review of these works on SFUDA is of great significance. In this paper, we provide a timely and systematic literature review of existing SFUDA approaches from a technical perspective. Specifically, we categorize current SFUDA studies into two groups, i.e., white-box SFUDA and black-box SFUDA, and further divide them into finer subcategories based on different learning strategies they use. We also investigate the challenges of methods in each subcategory, discuss the advantages/disadvantages of white-box and black-box SFUDA methods, conclude the commonly used benchmark datasets, and summarize the popular techniques for improved generalizability of models learned without using source data. We finally discuss several promising future directions in this field.
Topics: Benchmarking; Knowledge; Privacy
PubMed: 38490115
DOI: 10.1016/j.neunet.2024.106230 -
Journal of Medical Systems Feb 2024This systematic review examines the recent use of artificial intelligence, particularly machine learning, in the management of operating rooms. A total of 22 selected... (Review)
Review
This systematic review examines the recent use of artificial intelligence, particularly machine learning, in the management of operating rooms. A total of 22 selected studies from February 2019 to September 2023 are analyzed. The review emphasizes the significant impact of AI on predicting surgical case durations, optimizing post-anesthesia care unit resource allocation, and detecting surgical case cancellations. Machine learning algorithms such as XGBoost, random forest, and neural networks have demonstrated their effectiveness in improving prediction accuracy and resource utilization. However, challenges such as data access and privacy concerns are acknowledged. The review highlights the evolving nature of artificial intelligence in perioperative medicine research and the need for continued innovation to harness artificial intelligence's transformative potential for healthcare administrators, practitioners, and patients. Ultimately, artificial intelligence integration in operative room management promises to enhance healthcare efficiency and patient outcomes.
Topics: Humans; Artificial Intelligence; Operating Rooms; Neural Networks, Computer; Algorithms; Machine Learning
PubMed: 38353755
DOI: 10.1007/s10916-024-02038-2 -
Healthcare Analytics (New York, N.Y.) Nov 2023The unexpected and rapid spread of the COVID-19 pandemic has amplified the acceptance of remote healthcare systems such as telemedicine. Telemedicine effectively... (Review)
Review
The unexpected and rapid spread of the COVID-19 pandemic has amplified the acceptance of remote healthcare systems such as telemedicine. Telemedicine effectively provides remote communication, better treatment recommendation, and personalized treatment on demand. It has emerged as the possible future of medicine. From a privacy perspective, secure storage, preservation, and controlled access to health data with consent are the main challenges to the effective deployment of telemedicine. It is paramount to fully overcome these challenges to integrate the telemedicine system into healthcare. In this regard, emerging technologies such as blockchain and federated learning have enormous potential to strengthen the telemedicine system. These technologies help enhance the overall healthcare standard when applied in an integrated way. The primary aim of this study is to perform a systematic literature review of previous research on privacy-preserving methods deployed with blockchain and federated learning for telemedicine. This study provides an in-depth qualitative analysis of relevant studies based on the architecture, privacy mechanisms, and machine learning methods used for data storage, access, and analytics. The survey allows the integration of blockchain and federated learning technologies with suitable privacy techniques to design a secure, trustworthy, and accurate telemedicine model with a privacy guarantee.
PubMed: 37223223
DOI: 10.1016/j.health.2023.100192 -
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 -
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 -
BMJ Open Nov 2023To assess the current evidence on the potential of digital health interventions (DHIs) to improve adherence to oral antipsychotics among patients with schizophrenia by... (Review)
Review
OBJECTIVES
To assess the current evidence on the potential of digital health interventions (DHIs) to improve adherence to oral antipsychotics among patients with schizophrenia by assessing the methodologies, feasibility and effectiveness of DHIs as well as the perceptions of relevant stakeholders.
DESIGN
The scoping review was conducted based on the methodologies outlined by Levac and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines.
DATA SOURCES
PubMed, Embase, Web of Science, Scopus, CINAHL, PsycINFO and the Cochrane Library were searched in August 2023 to identify relevant publications from the previous decade.
ELIGIBILITY CRITERIA
Studies published in English focused on improving medication adherence among adult patients with schizophrenia or schizoaffective disorder via DHIs were selected. Protocols, editorials, comments, perspectives, reviews, correspondence and conference abstracts were excluded.
DATA EXTRACTION AND SYNTHESIS
The extracted data included general information about the study, framework, participants, features and strategies of DHIs, measurement tools for adherence used, and main findings.
RESULTS
In total, 64 studies were included in the qualitative synthesis. Features used in DHIs to improve medication adherence included phone calls, text messages, mobile apps, sensors, web-based platforms and electronic devices. Strategies included medication reminders and monitoring, providing medication-related information and suggestions, other illness management suggestions and individual support. Texting and mobile apps were commonly used as medication reminders and monitoring methods. Additionally, the use of sensors combined with other digital technologies has garnered significant attention. All the interventions were considered acceptable and feasible, and several were assessed in pilot trials. Preliminary findings suggest that DHIs could enhance medication adherence in patients with schizophrenia. However, further validation of their effectiveness is required.
CONCLUSION
DHIs are a promising approach to enhancing medication adherence among patients with schizophrenia. Future interventions should be interactive, focusing on user preference, experience and privacy.
Topics: Adult; Humans; Antipsychotic Agents; Schizophrenia; Text Messaging; Psychotic Disorders; Medication Adherence
PubMed: 37977861
DOI: 10.1136/bmjopen-2023-071984 -
Journal of the International AIDS... Jul 2023Pre-exposure prophylaxis (PrEP) is an important HIV prevention option. Two randomized trials have provided efficacy evidence for long-acting injectable cabotegravir... (Review)
Review
INTRODUCTION
Pre-exposure prophylaxis (PrEP) is an important HIV prevention option. Two randomized trials have provided efficacy evidence for long-acting injectable cabotegravir (CAB-LA) as PrEP. In considering CAB-LA as an additional PrEP modality for people at substantial risk of HIV, it is important to understand community response to injectable PrEP. We conducted a systematic review of values, preferences and perceptions of acceptability for injectable PrEP to inform global guidance.
METHODS
We searched nine databases and conference websites for peer-reviewed and grey literature (January 2010-September 2021). There were no restrictions on location. A two-stage review process assessed references against eligibility criteria. Data from included studies were organized by constructs from the Theoretical Framework of Acceptability.
RESULTS
We included 62 unique references. Most studies were observational, cross-sectional and qualitative. Over half of the studies were conducted in North America. Men who have sex with men were the most researched group. Most studies (57/62) examined injectable PrEP, including hypothetical injectables (55/57) or placebo products (2/57). Six studies examined CAB-LA specifically. There was overall interest in and often a preference for injectable PrEP, though there was variation within and across groups and regions. Many stakeholders indicated that injectable PrEP could help address adherence challenges associated with daily or on-demand dosing for oral PrEP and may be a better lifestyle fit for individuals seeking privacy, discretion and infrequent dosing. End-users reported concerns, including fear of needles, injection site pain and body location, logistical challenges and waning or incomplete protection.
DISCUSSION
Despite an overall preference for injectable PrEP, heterogeneity across groups and regions highlights the importance of enabling end-users to choose a PrEP modality that supports effective use. Like other products, preference for injectable PrEP may change over time and end-users may switch between prevention options. There will be a greater understanding of enacted preference as more end-users are offered anti-retroviral (ARV)-containing injectables. Future research should focus on equitable implementation, including real-time decision-making and how trained healthcare providers can support choice.
CONCLUSIONS
Given overall acceptability, injectable PrEP should be included as part of a menu of prevention options, allowing end-users to select the modality that suits their preferences, needs and lifestyle.
Topics: Male; Humans; Cross-Sectional Studies; Homosexuality, Male; Pre-Exposure Prophylaxis; Sexual and Gender Minorities; HIV Infections
PubMed: 37439057
DOI: 10.1002/jia2.26107