-
Psychiatric Rehabilitation Journal Sep 2017Internet (eHealth) and smartphone-based (mHealth) approaches to self-management for bipolar disorder are increasingly common. Evidence-based self-management strategies... (Review)
Review
OBJECTIVE
Internet (eHealth) and smartphone-based (mHealth) approaches to self-management for bipolar disorder are increasingly common. Evidence-based self-management strategies are available for bipolar disorder and provide a useful framework for reviewing existing eHealth/mHealth programs to determine whether these strategies are supported by current technologies. This review assesses which self-management strategies are most supported by technology.
METHOD
Based on 3 previous studies, 7 categories of self-management strategies related to bipolar disorder were identified, followed by a systematic literature review to identify existing eHealth and mHealth programs for this disorder. Searches were conducted by using PubMed, CINAHL, PsycINFO, EMBASE, and the Cochrane Database of Systematic Reviews for relevant peer-reviewed articles published January 2005 to May 2015. eHealth and mHealth programs were summarized and reviewed to identify which of the 7 self-management strategy categories were supported by eHealth or mHealth programs.
RESULTS
From 1,654 publications, 15 papers were identified for inclusion. From these, 9 eHealth programs and 2 mHealth programs were identified. The most commonly supported self-management strategy categories were "ongoing monitoring," "maintaining hope," "education," and "planning for and taking action"; the least commonly supported categories were "relaxation" and "maintaining a healthy lifestyle." eHealth programs appear to provide more comprehensive coverage of self-management strategies compared with mHealth programs.
CONCLUSIONS AND IMPLICATIONS FOR PRACTICE
Both eHealth and mHealth programs present a wide range of self-management strategies for bipolar disorder, although individuals seeking comprehensive interventions might be best served by eHealth programs, while those seeking more condensed and direct interventions might prefer mHealth programs. (PsycINFO Database Record
Topics: Bipolar Disorder; Humans; Internet; Medical Informatics Applications; Mobile Applications; Self-Management; Telemedicine
PubMed: 28594196
DOI: 10.1037/prj0000270 -
Frontiers in Artificial Intelligence 2021Well-curated datasets are essential to evidence based decision making and to the integration of artificial intelligence with human reasoning across disciplines. However,...
Well-curated datasets are essential to evidence based decision making and to the integration of artificial intelligence with human reasoning across disciplines. However, many sources of data remain siloed, unstructured, and/or unavailable for complementary and secondary research. Sysrev was developed to address these issues. First, Sysrev was built to aid in systematic evidence reviews (SER), where digital documents are evaluated according to a well defined process, and where Sysrev provides an easy to access, publicly available and free platform for collaborating in SER projects. Secondly, Sysrev addresses the issue of unstructured, siloed, and inaccessible data in the context of generalized data extraction, where human and machine learning algorithms are combined to extract insights and evidence for better decision making across disciplines. Sysrev uses FAIR - Findability, Accessibility, Interoperability, and Reuse of digital assets - as primary principles in design. Sysrev was developed primarily because of an observed need to reduce redundancy, reduce inefficient use of human time and increase the impact of evidence based decision making. This publication is an introduction to Sysrev as a novel technology, with an overview of the features, motivations and use cases of the tool. Sysrev. com is a FAIR motivated web platform for data curation and SER. Sysrev allows users to create data curation projects called "sysrevs" wherein users upload documents, define review tasks, recruit reviewers, perform review tasks, and automate review tasks. Sysrev is a web application designed to facilitate data curation and SERs. Thousands of publicly accessible Sysrev projects have been created, accommodating research in a wide variety of disciplines. Described use cases include data curation, managed reviews, and SERs.
PubMed: 34423285
DOI: 10.3389/frai.2021.685298 -
International Journal of Medical... Mar 2015The introduction of an information system integrated to bedside equipment requires significant financial and resource investment; therefore understanding the potential... (Review)
Review
The organizational and clinical impact of integrating bedside equipment to an information system: a systematic literature review of patient data management systems (PDMS).
OBJECTIVE
The introduction of an information system integrated to bedside equipment requires significant financial and resource investment; therefore understanding the potential impact is beneficial for decision-makers. However, no systematic literature reviews (SLRs) focus on this topic. This SLR aims to gather evidence on the impact of the aforementioned system, also known as a patient data management system (PDMS) on both organizational and clinical outcomes.
MATERIALS AND METHODS
A literature search was performed using the databases Medline/PubMed and CINHAL for English articles published between January 2000 and December 2012. A quality assessment was performed on articles deemed relevant for the SLR.
RESULTS
Eighteen articles were included in the SLR. Sixteen articles investigated the impact of a PDMS on the organizational outcomes, comprising descriptive, quantitative and qualitative studies. A PDMS was found to reduce the charting time, increase the time spent on direct patient care and reduce the occurrence of errors. Only two articles investigated the clinical impact of a PDMS. Both reported an improvement in clinical outcomes when a PDMS was integrated with a clinical decision support system (CDSS).
CONCLUSIONS
A PDMS has shown to offer many advantages in both the efficiency and the quality of care delivered to the patient. In addition, a PDMS integrated to a CDSS may improve clinical outcomes, although further studies are required for validation.
Topics: Critical Care; Decision Support Systems, Clinical; Efficiency, Organizational; Health Care Rationing; Health Information Exchange; Hospitals; Humans; Medical Errors; Point-of-Care Systems; Workflow
PubMed: 25601332
DOI: 10.1016/j.ijmedinf.2014.12.002 -
Autoimmunity Reviews May 2024Estimate the global prevalence of anti-Ro52-kDa/SSA (TRIM21) autoantibodies in systemic sclerosis (SSc), and describe the associated clinical phenotype, through a... (Meta-Analysis)
Meta-Analysis Review
Prevalence of anti-Ro52-kDa/SSA (TRIM21) antibodies and associated clinical phenotype in systemic sclerosis: Data from a French cohort, a systematic review and meta-analysis.
OBJECTIVES
Estimate the global prevalence of anti-Ro52-kDa/SSA (TRIM21) autoantibodies in systemic sclerosis (SSc), and describe the associated clinical phenotype, through a systematic review and meta-analysis of published reports and new data from our French cohort.
METHODS
Anti-TRIM21 seropositivity and associated SSc characteristics were assessed in a cross-sectional study including 300 patients of Lille University Hospital. A systematic review of the literature was performed in Pubmed and Embase, followed by a meta-analysis, using data on prevalence, clinical/demographical/biological characteristics of SSc patients and the type of assay used for anti-TRIM21 antibodies detection (PROSPERO n° CRD42021223719).
FINDINGS
In the cross-sectional study, anti-TRIM21 antibodies prevalence was 26% [95%CI: 21; 31]. Anti-centromere antibodies were the most frequent SSc specific autoantibodies coexisting with anti-TRIM21. Patients with anti-TRIM21 antibodies were more frequently women (91% vs 77%, p = 0.006), more likely to present an associated Sjögren's syndrome (19% vs 7%, p < 0.001), had a higher rate of pulmonary arterial hypertension (PAH) (15% vs 6%, p = 0.017) and a greater frequency of digestive complications such as dysphagia (12% vs 5%, p = 0.038) or nausea/vomiting (10% vs 3%, p = 0.009) than anti-TRIM21 negative patients. Thirty-five articles corresponding to a total of 11,751 SSc patients were included in the meta-analysis. In this population, the overall seroprevalence of anti-TRIM21 antibodies was 23% [95%CI: 21; 27] with a high degree of heterogeneity (I: 93% Phet: <0.0001), partly explained by the methods of detection. Anti-TRIM21 seropositivity was positively associated with female sex (OR: 1.60 [95%CI: 1.25, 2.06]), limited cutaneous subset (OR: 1.29 [1.04, 1.61]), joint manifestations (OR: 1.33 [1.05, 1.68]), pulmonary hypertension (PH) (OR: 1.82 [1.42, 2.33]), and interstitial lung disease (ILD) (OR: 1.31 [1.07, 1.60]).
INTERPRETATION
Anti-TRIM21 antibodies frequently co-exist with usual SSc antibodies, but are independently associated to a higher risk of cardio-pulmonary complications. The presence of these autoantibodies should therefore be considered when assessing the risk of developing PH and ILD, and deserves further studies on appropriate screening and follow-up of patients.
Topics: Humans; Scleroderma, Systemic; Autoantibodies; Ribonucleoproteins; France; Phenotype; Antibodies, Antinuclear; Prevalence; Female; Cross-Sectional Studies; Male
PubMed: 38555075
DOI: 10.1016/j.autrev.2024.103536 -
Diabetic Medicine : a Journal of the... Nov 2019Time preferences, i.e. individuals' degree of patience/impatience in intertemporal choice, have been found to be associated with suboptimal health behaviours and health...
AIM
Time preferences, i.e. individuals' degree of patience/impatience in intertemporal choice, have been found to be associated with suboptimal health behaviours and health outcomes such as smoking, physical inactivity, unhealthy food intake and obesity. In this systematic review, we aimed to synthesise reported associations between time preferences, diabetes self-management behaviours, including use of diabetes technology, and outcomes.
METHODS
We searched MEDLINE, EMBASE, PsycINFO, CINAHL, EconLit and all databases in the Web of Science Core Collection. Peer-reviewed studies of people with diabetes that included at least one diabetes-related behaviour or outcome and a measure of time preferences were included. Non-English language studies were excluded.
RESULTS
A total of 961 records were identified, of which 12 articles were included. Three studies analysed both time-consistent and time-inconsistent preferences, three studies solely analysed time-inconsistent preferences and six studies did not explicitly define a time preference model. Measured outcomes across studies included self-care activities, such as medication-taking, exercising and eating a healthy diet, and biomedical outcomes, such as HbA and diabetes-related complications. There were 10 cross-sectional studies and two panel-data studies. No studies explicitly analysed the relationship between time preferences and diabetes technology use.
CONCLUSIONS
Associations between measures of time preferences, diabetes self-management behaviours and clinical outcomes exist. Higher discount rates determined by both time-consistent and time-inconsistent models predict less diabetes-related self-care and worse outcomes. These findings may add to explanations of the observed variation in diabetes-related health and provide new insights for tailoring interventions and policies aimed at improving diabetes self-management.
Topics: Alcohol Drinking; Diabetes Mellitus; Exercise; Health Behavior; Humans; Obesity; Patient Acceptance of Health Care; Patient Compliance; Patient Outcome Assessment; Self-Management; Time Factors
PubMed: 31392757
DOI: 10.1111/dme.14102 -
Use of Mobile Crowdsensing in Disaster Management: A Systematic Review, Challenges, and Open Issues.Sensors (Basel, Switzerland) Feb 2023With the increasing efforts to utilize information and communication technologies (ICT) in disaster management, the massive amount of heterogeneous data that is... (Review)
Review
With the increasing efforts to utilize information and communication technologies (ICT) in disaster management, the massive amount of heterogeneous data that is generated through ubiquitous sensors paves the way for fast and informed decisions in the case of disasters. Utilization of the big "sensed" data leads to an effective and efficient management of disaster situations so as to prevent human and economic losses. The advancement of built-in sensing technologies in smart mobile devices enables crowdsourcing of sensed data, which is known as mobile crowdsensing (MCS). This systematic literature review investigates the use of mobile crowdsensing in disaster management on the basis of the built-in sensor types in smart mobile devices, disaster management categories, and the disaster management cycle phases (i.e., mitigation, preparedness, response, and recovery activities). Additionally, this work seeks to unveil the frameworks or models that can potentially guide disaster management authorities towards integrating crowd-sensed data with their existing decision-support systems. The vast majority of the existing studies are conceptual as they highlight a challenge in experimental testing of the disaster management solutions in real-life settings, and there is little emphasis on the use cases of crowdsensing through smartphone sensors in disaster incidents. In light of a thorough review, we provide and discuss future directions and open issues for mobile crowdsensing-aided disaster management.
PubMed: 36772738
DOI: 10.3390/s23031699 -
Pain Medicine (Malden, Mass.) Oct 2009To review the literature addressing effective care for acute pain in inpatients on medical wards. (Meta-Analysis)
Meta-Analysis Review
OBJECTIVE
To review the literature addressing effective care for acute pain in inpatients on medical wards.
METHODS
We searched Medline, PubMed Clinical Queries, and the Cochrane Database for systematic reviews published in 1996 through April 2007 on the assessment and management of acute pain in inpatients, including patients with impaired self-report or chemical dependencies. We conducted a focused search for studies on the timing and frequency of assessment, and on the use of patient-controlled analgesia (PCA) for nonsurgical pain. Two investigators performed a critical analysis of the literature and compiled narrative summaries to address the key questions.
RESULTS
We found no evidence that directly linked the timing, frequency, or method of pain assessment with outcomes or safety in medical inpatients. There is good evidence that treating abdominal pain does not compromise timely diagnosis and treatment of the surgical abdomen. Pain management teams and other systemwide interventions improve assessment and use of analgesics, but do not clearly affect pain outcomes. The safety and effectiveness of PCA in medical patients have not been studied. There is weak evidence that most cognitively impaired individuals can understand at least one self-assessment measure. Almost no evidence is available to guide management of pain in delirium. Evidence for managing pain in patients with substance abuse disorders or chronic opioid use is weak, being derived from case reports, retrospective studies, and expert opinion.
CONCLUSIONS
Pain is a prevalent problem for medical inpatients. Clinical research is needed to guide the assessment and management of pain in this setting.
Topics: Adult; Humans; Incidence; Inpatients; Pain; Pain Management; Pain Measurement; Practice Patterns, Physicians'; Prevalence; Risk Assessment; Risk Factors; Treatment Outcome
PubMed: 19818030
DOI: 10.1111/j.1526-4637.2009.00718.x -
Veterinary Sciences Sep 2020Owner-reported behavioural observations form an essential part of the veterinarians' diagnosis and treatment plan. The way we train and manage horses affects their... (Review)
Review
Owner-reported behavioural observations form an essential part of the veterinarians' diagnosis and treatment plan. The way we train and manage horses affects their behaviour and, in turn, their health and welfare. Current horse training and management practices are largely driven by traditional techniques and longstanding methodologies. These approaches generally lack an evidence base for evaluation purposes. The absence of evidence and evaluation contributes to the persistent use of risky practices and this, in turn, increases risk of potential harms for both horse and rider, and fuels questioning of the equine industry's current social license to operate. Objective evidence is required to make training and management decisions based on demonstrable best practice. Large-scale experimental or intervention studies using horses are generally not practical because of the associated costs and logistics of gaining ethical approval. Small studies generally lack statistical power and are subject to the effects of many forms of bias that demand caution in the interpretation of any observed effects. An alternative to collecting large amounts of empirical data is the use of owner-reported observations via online survey. Horse owners are ideally placed to report on the domestic equine triad of training, management, and behaviour. The current article highlights three sources of potential bias in a systematic review of literature on large-scale online studies of horse owners' observational reports that met the following selection criteria: English-language, published, peer-reviewed articles reporting on studies with over 1000 respondents and open access to the survey instrument. The online surveys were evaluated for three common forms of bias: recall, confirmation, and sampling bias. This review reveals that online surveys are useful for gathering data on the triad of horse training, management, and behaviour. However, current use of online surveys to collect data on equitation science (including horse training, management, and behaviour) could be improved by using a standardised and validated tool. Such a tool would facilitate comparisons among equine and equitation science studies, thus advancing our understanding of the impacts of training and management on horse behaviour. The authors of the current review suggest the use of a standardised behavioural and management assessment tool for horses. Such a tool would help define what constitutes normal behaviour within geographically disparate populations of horses, leading to improvements in rider safety and horse welfare.
PubMed: 32971754
DOI: 10.3390/vetsci7030140 -
Frontiers in Psychiatry 2021Individual participant data meta-analyses (IPD-MAs) include the raw data from relevant randomised clinical trials (RCTs) and involve secondary analyses of the data....
Individual participant data meta-analyses (IPD-MAs) include the raw data from relevant randomised clinical trials (RCTs) and involve secondary analyses of the data. Performed since the late 1990s, ~50 such meta-analyses have been carried out in psychiatry, mostly in the field of treatment. IPD-MAs are particularly relevant for three objectives: (1) evaluation of the average effect of an intervention by combining effects from all included trials, (2) evaluation of the heterogeneity of an intervention effect and sub-group analyses to approach personalised psychiatry, (3) mediation analysis or surrogacy evaluation to replace a clinical (final) endpoint for the evaluation of new treatments with intermediate or surrogate endpoints. The objective is to describe the interest and the steps of an IPD-MA method applied to the field of psychiatric therapeutic research. The method is described in three steps. First, the identification of the relevant trials with an explicit description of the inclusion/exclusion criteria for the RCT to be incorporated in the IPD-MA and a definition of the intervention, the population, the context and the relevant points (outcomes or moderators). Second, the data management with the standardisation of collected variables and the evaluation and the assessment of the risk-of-bias for each included trial and of the global risk. Third, the statistical analyses and their interpretations, depending on the objective of the meta-analysis. All steps are illustrated with examples in psychiatry for treatment issues, excluding study protocols. The meta-analysis of individual patient data is challenging. Only strong collaborations between all stakeholders can make such a process efficient. An "ecosystem" that includes all stakeholders (questions of interest prioritised by the community, funders, trialists, journal editors, institutions, …) is required. International medical societies can play a central role in favouring the emergence of such communities.
PubMed: 34393841
DOI: 10.3389/fpsyt.2021.644980 -
Clinical Microbiology and Infection :... Dec 2020Bacterial co-pathogens are commonly identified in viral respiratory infections and are important causes of morbidity and mortality. The prevalence of bacterial infection... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Bacterial co-pathogens are commonly identified in viral respiratory infections and are important causes of morbidity and mortality. The prevalence of bacterial infection in patients infected with SARS-CoV-2 is not well understood.
AIMS
To determine the prevalence of bacterial co-infection (at presentation) and secondary infection (after presentation) in patients with COVID-19.
SOURCES
We performed a systematic search of MEDLINE, OVID Epub and EMBASE databases for English language literature from 2019 to April 16, 2020. Studies were included if they (a) evaluated patients with confirmed COVID-19 and (b) reported the prevalence of acute bacterial infection.
CONTENT
Data were extracted by a single reviewer and cross-checked by a second reviewer. The main outcome was the proportion of COVID-19 patients with an acute bacterial infection. Any bacteria detected from non-respiratory-tract or non-bloodstream sources were excluded. Of 1308 studies screened, 24 were eligible and included in the rapid review representing 3338 patients with COVID-19 evaluated for acute bacterial infection. In the meta-analysis, bacterial co-infection (estimated on presentation) was identified in 3.5% of patients (95%CI 0.4-6.7%) and secondary bacterial infection in 14.3% of patients (95%CI 9.6-18.9%). The overall proportion of COVID-19 patients with bacterial infection was 6.9% (95%CI 4.3-9.5%). Bacterial infection was more common in critically ill patients (8.1%, 95%CI 2.3-13.8%). The majority of patients with COVID-19 received antibiotics (71.9%, 95%CI 56.1 to 87.7%).
IMPLICATIONS
Bacterial co-infection is relatively infrequent in hospitalized patients with COVID-19. The majority of these patients may not require empirical antibacterial treatment.
Topics: Asia; Bacteria; Bacterial Infections; COVID-19; Coinfection; Critical Illness; Data Management; Female; Humans; Male; Pandemics; Prevalence; Respiratory Tract Infections; United States
PubMed: 32711058
DOI: 10.1016/j.cmi.2020.07.016