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Npj Mental Health Research Sep 2023Post-traumatic stress disorder (PTSD) is frequently underdiagnosed due to its clinical and biological heterogeneity. Worldwide, many people face barriers to accessing... (Review)
Review
Post-traumatic stress disorder (PTSD) is frequently underdiagnosed due to its clinical and biological heterogeneity. Worldwide, many people face barriers to accessing accurate and timely diagnoses. Machine learning (ML) techniques have been utilized for early assessments and outcome prediction to address these challenges. This paper aims to conduct a systematic review to investigate if ML is a promising approach for PTSD diagnosis. In this review, statistical methods were employed to synthesize the outcomes of the included research and provide guidance on critical considerations for ML task implementation. These included (a) selection of the most appropriate ML model for the available dataset, (b) identification of optimal ML features based on the chosen diagnostic method, (c) determination of appropriate sample size based on the distribution of the data, and (d) implementation of suitable validation tools to assess the performance of the selected ML models. We screened 3186 studies and included 41 articles based on eligibility criteria in the final synthesis. Here we report that the analysis of the included studies highlights the potential of artificial intelligence (AI) in PTSD diagnosis. However, implementing AI-based diagnostic systems in real clinical settings requires addressing several limitations, including appropriate regulation, ethical considerations, and protection of patient privacy.
PubMed: 38609504
DOI: 10.1038/s44184-023-00035-w -
Health Promotion and Chronic Disease... Apr 2024Indigenous people in Canada encounter negative treatment when accessing primary health care (PHC). Despite several qualitative accounts of these experiences, there still...
INTRODUCTION
Indigenous people in Canada encounter negative treatment when accessing primary health care (PHC). Despite several qualitative accounts of these experiences, there still has not been a qualitative review conducted on this topic. In this qualitative systematic review, we aimed to explore Indigenous people's experiences in Canada with PHC services, determine urban versus rural or remote differences and identify recommendations for quality improvement.
METHODS
This review was guided by the Joanna Briggs Institute's methodology for systematic reviews of qualitative evidence. MEDLINE, CINAHL, PubMed, PsycInfo, Embase and Web of Science as well as grey literature and ancestry sources were used to identify relevant articles. Ancestry sources were obtained through reviewing the reference lists of all included articles and determining the ones that potentially met the eligibility criteria. Two independent reviewers conducted the initial and full text screening, data extraction and quality assessment. Once all data were gathered, they were synthesized following the meta-aggregation approach (PROSPERO CRD42020192353).
RESULTS
The search yielded a total of 2503 articles from the academic databases and 12 articles from the grey literature and ancestry sources. Overall, 22 articles were included in this review. Three major synthesized findings were revealed-satisfactory experiences, discriminatory attitudes and systemic challenges faced by Indigenous patients-along with one synthesized finding on their specific recommendations.
CONCLUSION
Indigenous people value safe, accessible and respectful care. The discrimination and racism they face negatively affect their overall health and well-being. Hence, it is crucial that changes in health care practice, structures and policy development as well as systemic transformation be implemented immediately.
Topics: Humans; Canada; Databases, Factual; Primary Health Care; Indigenous Canadians
PubMed: 38597804
DOI: 10.24095/hpcdp.44.4.01 -
Digital Health 2024Many clinical trials fail because of poor recruitment and enrollment which can directly impact the success of biomedical and clinical research outcomes. Options to... (Review)
Review
BACKGROUND
Many clinical trials fail because of poor recruitment and enrollment which can directly impact the success of biomedical and clinical research outcomes. Options to leverage digital technology for improving clinical trial management are expansive, with potential benefits for improving access to clinical trials, encouraging trial diversity and inclusion, and potential cost-savings through enhanced efficiency.
OBJECTIVES
This systematic review has two key aims: (1) identify and describe the digital technologies applied in clinical trial recruitment and enrollment and (2) evaluate evidence of these technologies addressing the recruitment and enrollment of racial and ethnic minority groups.
METHODS
We conducted a cross-disciplinary review of articles from PubMed, IEEE Xplore, and ACM Digital Library, published in English between January 2012 and July 2022, using MeSH terms and keywords for digital health, clinical trials, and recruitment and enrollment. Articles unrelated to technology in the recruitment/enrollment process or those discussing recruitment/enrollment without technology aspects were excluded.
RESULTS
The review returned 614 results, with 21 articles (four reviews and 17 original research articles) deemed suitable for inclusion after screening and full-text review. To address the first objective, various digital technologies were identified and characterized, which included articles with more than one technology subcategory including (a) multimedia presentations (19%, = 4); (b) mobile applications (14%, = 3); (c) social media platforms (29%, = 6); (d) machine learning and computer algorithms (19%, = 4); (e) e-consenting (24%, = 5); (f) blockchain (5%, = 1); (g) web-based programs (24%, = 5); and (h) virtual messaging (24%, = 5). Additionally, subthemes, including specific diseases or conditions addressed, privacy and regulatory concerns, cost/benefit analyses, and ethnic and minority recruitment considerations, were identified and discussed. Limited research was found to support a particular technology's effectiveness in racial and ethnic minority recruitment and enrollment.
CONCLUSION
Results from this review illustrate that several types of technology are currently being explored and utilized in clinical trial recruitment and enrollment stages. However, evidence supporting the use of digital technologies is varied and requires further research and evaluation to identify the most valuable opportunities for encouraging diversity in clinical trial recruitment and enrollment practices.
PubMed: 38559578
DOI: 10.1177/20552076241242390 -
International Journal of Medical... Jun 2024Clinical Decision Support Systems (CDSSs) are electronic systems used to conduct assessments based on patient characteristics and to offer treatment recommendations for... (Review)
Review
BACKGROUND
Clinical Decision Support Systems (CDSSs) are electronic systems used to conduct assessments based on patient characteristics and to offer treatment recommendations for clinicians to consider during their decision-making processes. CDSSs are needed by mental health helpline services to optimise service delivery for clients and counsellors, while also collecting the data needed for the administration of the service. The aim of this systematic review was to provide a comprehensive overview of the design and implementation of CDSSs in mental health helpline services, to identify current issues in their design and implementation, and to provide recommendations that may address any identified issues.
MATERIALS AND METHODS
Keywords related to mental health, helplines and CDSS were searched in three databases in April 2022 and September 2023. In total, 21 articles published between 1987 and 2023 met the inclusion criteria.
RESULTS
The objectives of the mental health helplines services included in this study included suicide risk reduction, diagnosis, treatment and monitoring of mental health disorders, and support of clinicians or counsellors in making better and more accurate decisions by incorporating real-time data analysis. All included studies demonstrated co-design activities, however, the level and degree of end-user involvement differed across the studies. The factors that impact CDSS implementation success depend on the design and implementation approach, user experience and context. CDSS evaluations in the included studies assessed reliability, utility, user friendlessness, cost-effectivenessand participant satisfaction. Few studies considered data privacy and integration issues.
CONCLUSION
More interactive methods should be adopted during the design of CDSSs for mental health helpline services. Increased frequency and intensity of user participation in system design, that goes beyond providing feedback on research materials, enables user opinions to be fully understood and addressed. Comprehensive frameworks should be developed to guide requirements gathering, system design and system evaluation practices. These factors are interrelated and may impact implementation success. From the outset therefore, the design of a CDSS in the mental health helpline domain should consider the full system development cycle.
Topics: Humans; Decision Support Systems, Clinical; Mental Health; Reproducibility of Results; Mental Health Services
PubMed: 38552266
DOI: 10.1016/j.ijmedinf.2024.105416 -
JMIR Mental Health Mar 2024Suicide safety planning is an evidence-based approach used to help individuals identify strategies to keep themselves safe during a mental health crisis. This study...
BACKGROUND
Suicide safety planning is an evidence-based approach used to help individuals identify strategies to keep themselves safe during a mental health crisis. This study systematically reviewed the literature focused on mobile health (mHealth) suicide safety planning apps.
OBJECTIVE
This study aims to evaluate the extent to which apps integrated components of the safety planning intervention (SPI), and if so, how these safety planning components were integrated into the design-based features of the apps.
METHODS
Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, we systematically analyzed 14 peer-reviewed studies specific to mHealth apps for suicide safety planning. We conducted an analysis of the literature to evaluate how the apps incorporated SPI components and examined similarities and differences among the apps by conducting a comparative analysis of app features. An independent review of SPI components and app features was conducted by downloading the available apps.
RESULTS
Most of the mHealth apps (5/7, 71%) integrated SPI components and provided customizable features that expanded upon traditional paper-based safety planning processes. App design features were categorized into 5 themes, including interactive features, individualized user experiences, interface design, guidance and training, and privacy and sharing. All apps included access to community supports and revisable safety plans. Fewer mHealth apps (3/7, 43%) included interactive features, such as associating coping strategies with specific stressors. Most studies (10/14, 71%) examined the usability, feasibility, and acceptability of the safety planning mHealth apps. Usability findings were generally positive, as users often found these apps easy to use and visually appealing. In terms of feasibility, users preferred using mHealth apps during times of crisis, but the continuous use of the apps outside of crisis situations received less support. Few studies (4/14, 29%) examined the effectiveness of mHealth apps for suicide-related outcomes. Positive shifts in attitudes and desire to live, improved coping strategies, enhanced emotional stability, and a decrease in suicidal thoughts or self-harm behaviors were examined in these studies.
CONCLUSIONS
Our study highlights the need for researchers, clinicians, and app designers to continue to work together to align evidence-based research on mHealth suicide safety planning apps with lessons learned for how to best deliver these technologies to end users. Our review brings to light mHealth suicide safety planning strategies needing further development and testing, such as lethal means guidance, collaborative safety planning, and the opportunity to embed more interactive features that leverage the advanced capabilities of technology to improve client outcomes as well as foster sustained user engagement beyond a crisis. Although preliminary evidence shows that these apps may help to mitigate suicide risk, clinical trials with larger sample sizes and more robust research designs are needed to validate their efficacy before the widespread adoption and use.
Topics: Humans; Mobile Applications; Self-Injurious Behavior; Suicidal Ideation; Suicide; Telemedicine
PubMed: 38546711
DOI: 10.2196/52763 -
EClinicalMedicine May 2024To receive the best care, people share their health data (HD) with their health practitioners (known as sharing HD for primary purposes). However, during the past two...
BACKGROUND
To receive the best care, people share their health data (HD) with their health practitioners (known as sharing HD for primary purposes). However, during the past two decades, sharing for other (i.e., secondary) purposes has become of great importance in numerous fields, including public health, personalized medicine, research, and development. We aimed to conduct the first comprehensive overview of all studies that investigated people's HD sharing attitudes-along with associated barriers/motivators and significant influencing factors-for all data types and across both primary and secondary uses.
METHODS
We searched PubMed, MEDLINE, PsycINFO, Web of Science, EMBASE, and CINAHL for relevant studies published in English between database inception and February 28, 2023, using a predefined set of keywords. Studies were included, regardless of their design, if they reported outcomes related to attitudes towards sharing HD. We extracted key data from the included studies, including the type of HD involved and findings related to: HD sharing attitudes (either in general or depending on type of data/user); barriers/motivators/benefits/concerns of the study participants; and sociodemographic and other variables that could impact HD sharing behaviour. The qualitative synthesis was conducted by dividing the studies according to the data type (resulting in five subgroups) as well as the purpose the data sharing was focused on (primary, secondary or both). The Newcastle-Ottawa Scale (NOS) was used to assess the quality of non-randomised studies. This work was registered with PROSPERO, CRD42023413822.
FINDINGS
Of 2109 studies identified through our search, 116 were included in the qualitative synthesis, yielding a total of 228,501 participants and various types of HD represented: person-generated HD (n = 17 studies and 10,771 participants), personal HD in general (n = 69 studies and 117,054 participants), Biobank data (n = 7 studies and 27,073 participants), genomic data (n = 13 studies and 54,716 participants), and miscellaneous data (n = 10 studies and 18,887 participants). The majority of studies had a moderate level of quality (83 [71.6%] of 116 studies), but varying levels of quality were observed across the included studies. Overall, studies suggest that sharing intentions for primary purposes were observed to be high regardless of data type, and it was higher than sharing intentions for secondary purposes. Sharing for secondary purposes yielded variable findings, where both the highest and the lowest intention rates were observed in the case of studies that explored sharing biobank data (98% and 10%, respectively). Several influencing factors on sharing intentions were identified, such as the type of data recipient, data, consent. Further, concerns related to data sharing that were found to be mutual for all data types included privacy, security, and data access/control, while the perceived benefits included those related to improvements in healthcare. Findings regarding attitudes towards sharing varied significantly across sociodemographic factors and depended on data type and type of use. In most cases, these findings were derived from single studies and therefore warrant confirmations from additional studies.
INTERPRETATION
Sharing health data is a complex issue that is influenced by various factors (the type of health data, the intended use, the data recipient, among others) and these insights could be used to overcome barriers, address people's concerns, and focus on spreading awareness about the data sharing process and benefits.
FUNDING
None.
PubMed: 38533128
DOI: 10.1016/j.eclinm.2024.102551 -
Frontiers in Public Health 2024To review and synthesize qualitative research exploring patients' safe experience and construct a model to present barriers and facilitators to feeling safe for...
OBJECTIVES
To review and synthesize qualitative research exploring patients' safe experience and construct a model to present barriers and facilitators to feeling safe for inpatients.
DESIGN
A qualitative met-synthesis.
METHODS
We conducted a systematic electronic search of articles published in English with no date limitation across five databases (Ovid MEDLINE, EMBASE, Web of Science, CINAIL via EBSCO, and PsyINFO) in May 2023. Qualitative research focused on the safe experiences of inpatients was considered. Systematic searches yielded 8,132 studies, of which 16 articles were included. Two reviewers independently extracted and analyzed data. Qualitative meta-synthesis was performed through line-by-line coding of original texts, organizing codes into descriptive themes, and generating analytical themes.
RESULTS
We identified four themes and 11 sub-themes. Across the four themes, control included a barrier (Uncertainty) and two facilitators (Patient participation and safe care); responsible included three facilitators (Confidence in the profession, care for, and responsive); dignity included two barriers (Privacy and Neglect); stability included a barrier (Potential risk), and two facilitators (Harmonious and safe culture). We constructed a model to present the logical connection between these themes and related barriers and facilitators.
CONCLUSION
Feeling safe for inpatients is a complex perception, including four themes: control, responsible, dignity, and stability. Surrounding four themes and related barriers and facilitators, we outline principles for creating a safe environment and present strategies for improving patients' hospitalization experience and ensuring patient safety.
CLINICAL RELEVANCE
This review provides valuable insight into the clinical practice and health policy and helps medical staff to identify and overcome the potential barriers to implementing interventions in safe care. In addition, the model comprehensively describes the nature and dimensions of feeling safe, informing high-quality care service and related research.
SYSTEMATIC REVIEW REGISTRATION
Identifier, CRD42023435489.
Topics: Humans; Inpatients; Medical Staff
PubMed: 38481849
DOI: 10.3389/fpubh.2024.1308258 -
Journal of Pharmacy & Pharmaceutical... 2024This review aimed to assess the current use and acceptance of real-world data (RWD) and real-world evidence (RWE) in health technology assessment (HTA) process. It...
Real-world data: a comprehensive literature review on the barriers, challenges, and opportunities associated with their inclusion in the health technology assessment process.
This review aimed to assess the current use and acceptance of real-world data (RWD) and real-world evidence (RWE) in health technology assessment (HTA) process. It additionally aimed to discern stakeholders' viewpoints concerning RWD and RWE in HTA and illuminate the obstacles, difficulties, prospects, and consequences associated with the incorporation of RWD and RWE into the realm of HTA. A comprehensive PRISMA-based systematic review was performed in July 2022 in PubMed/Medline, Scopus, IDEAS-RePEc, International HTA database, and Centre for Reviews and Dissemination with supplementary search in Google Scholar and international organization websites. The review included pre-determined inclusion criteria while the selection of eligible studies, the data extraction process and quality assessment were carried out using standardized and transparent methods. Twenty-nine ( = 29) studies were included in the review out of 2,115 studies identified by the search strategy. In various global contexts, disparities in RWD utilization were evident, with randomized controlled trials (RCTs) serving as the primary evidence source. RWD and RWE played pivotal roles, surpassing relative effectiveness assessments (REAs) and significantly influencing decision-making and cost-effectiveness analyses. Identified challenges impeding RWD integration into HTA encompassed limited local data access, complexities in non-randomized trial design, data quality, privacy, and fragmentation. Addressing these is imperative for optimal RWD utilization. Incorporating RWD/RWE in HTA yields multifaceted advantages, enhancing understanding of treatment efficacy, resource utilization, and cost analysis, particularly via patient registries. RWE complements assessments of advanced therapy medicinal products (ATMPs) and rare diseases. Local data utilization strengthens HTA, bridging gaps when RCT data is lacking. RWD aids medical device decision-making, cancer drug reassessment, and indirect treatment comparisons. Challenges include data availability, stakeholder acceptance, expertise, and privacy. However, standardization, training, collaboration, and guidance can surmount these barriers, fostering enhanced RWD utilization in HTA. This study highlights the intricate global landscape of RWD and RWE acceptance in HTA. Recognizing regional nuances, addressing methodological challenges, and promoting collaboration are pivotal, among others, for leveraging RWD and RWE effectively in healthcare decision-making.
Topics: Humans; Technology Assessment, Biomedical; Data Accuracy
PubMed: 38481726
DOI: 10.3389/jpps.2024.12302 -
International Journal of Molecular... Mar 2024This systematic review addresses the use of ( in the symptomatological intervention of neurodegenerative disease. The existence of gut microbiota dysbiosis has been... (Review)
Review
This systematic review addresses the use of ( in the symptomatological intervention of neurodegenerative disease. The existence of gut microbiota dysbiosis has been associated with systemic inflammatory processes present in neurodegenerative disease, creating the opportunity for new treatment strategies. This involves modifying the strains that constitute the gut microbiota to enhance synaptic function through the gut-brain axis. Recent studies have evaluated the beneficial effects of the use of on motor and cognitive symptomatology, alone or in combination. This systematic review includes 20 research articles ( = 3 in human and = 17 in animal models). The main result of this research was that the use of alone or in combination produced improvements in symptomatology related to neurodegenerative disease. However, one of the studies included reported negative effects after the administration of . This systematic review provides current and relevant information about the use of this probiotic in pathologies that present neurodegenerative processes such as Alzheimer's disease, Parkinson's disease and Multiple Sclerosis.
Topics: Animals; Humans; Neurodegenerative Diseases; Access to Information; Alzheimer Disease; Parkinson Disease; Lactobacillus plantarum; Probiotics
PubMed: 38474254
DOI: 10.3390/ijms25053010 -
Nature Communications Mar 2024Cloud-based personal health records increase globally. The GPOC series introduces the concept of a Global Patient co-Owned Cloud (GPOC) of personal health records. Here,... (Meta-Analysis)
Meta-Analysis
Cloud-based personal health records increase globally. The GPOC series introduces the concept of a Global Patient co-Owned Cloud (GPOC) of personal health records. Here, we present the GPOC series' Prospective Register of Systematic Reviews (PROSPERO) registered and Preferred Reporting Items Systematic and Meta-Analyses (PRISMA)-guided systematic review and meta-analysis. It examines cloud-based personal health records and factors such as data security, efficiency, privacy and cost-based measures. It is a meta-analysis of twelve relevant axes encompassing performance, cryptography and parameters based on efficiency (runtimes, key generation times), security (access policies, encryption, decryption) and cost (gas). This aims to generate a basis for further research, a GPOC sandbox model, and a possible construction of a global platform. This area lacks standard and shows marked heterogeneity. A consensus within this field would be beneficial to the development of a GPOC. A GPOC could spark the development and global dissemination of artificial intelligence in healthcare.
Topics: Humans; Artificial Intelligence; Health Records, Personal; Privacy; Computer Security
PubMed: 38467643
DOI: 10.1038/s41467-024-46503-5