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BMJ Open Jun 2022Identify and describe the available evidence on the effects food systems interventions on food security and nutrition outcomes in low-income and middle-income countries.
OBJECTIVE
Identify and describe the available evidence on the effects food systems interventions on food security and nutrition outcomes in low-income and middle-income countries.
METHODS
An adapted version of the high-level panel of experts food systems framework defined the interventions and outcomes included studies. Included study designs were experimental and quasi-experimental quantitative impact evaluations and systematic reviews. Following standards for evidence gap maps developed by 3ie, a systematic search of 17 academic databases and 31 sector-specific repositories in May 2020 identified articles for inclusion. Trained consultants screened titles/abstracts, then full texts of identified articles. Studies meeting eligibility criteria had meta-data systematically extracted and were descriptively analysed. Systematic reviews were critically appraised.
RESULTS
The map includes 1838 impact evaluations and 178 systematic reviews. The most common interventions, with over 100 impact evaluations and 20 systematic reviews each, were: provision of supplements, fortification, nutrition classes, direct provision of foods and peer support/counselling. Few studies addressed national-level interventions or women's empowerment. The most common final outcomes were: anthropometry, micronutrient status, and diet quality and adequacy. Intermediate outcomes were less studied.Most evaluations were conducted in sub-Saharan Africa (33%) or South Asia (20%). Many studies occurred in lower-middle-income countries (43%); few (7%) were in fragile countries. Among studies in a specific age group, infants were most frequently included (19%); 14% of these also considered mothers.Few evaluations considered qualitative or cost analysis; 75% used randomisation as the main identification strategy.
DISCUSSION
The uneven distribution of research means that some interventions have established impacts while other interventions, often affecting large populations, are underevaluated. Areas for future research include the evaluation of national level policies, evaluation of efforts to support women's empowerment within the food system, and the synthesis of dietary quality. Quasi-experimental approaches should be adopted to evaluate difficult to randomise interventions.
Topics: Developing Countries; Dietary Supplements; Female; Humans; Income; Infant; Micronutrients; Poverty
PubMed: 35732381
DOI: 10.1136/bmjopen-2021-055062 -
PeerJ 2023The emerging field of environmental DNA (eDNA) research lacks universal guidelines for ensuring data produced are FAIR-findable, accessible, interoperable, and...
The emerging field of environmental DNA (eDNA) research lacks universal guidelines for ensuring data produced are FAIR-findable, accessible, interoperable, and reusable-despite growing awareness of the importance of such practices. In order to better understand these data usability challenges, we systematically reviewed 60 peer reviewed articles conducting a specific subset of eDNA research: metabarcoding studies in marine environments. For each article, we characterized approximately 90 features across several categories: general article attributes and topics, methodological choices, types of metadata included, and availability and storage of sequence data. Analyzing these characteristics, we identified several barriers to data accessibility, including a lack of common context and vocabulary across the articles, missing metadata, supplementary information limitations, and a concentration of both sample collection and analysis in the United States. While some of these barriers require significant effort to address, we also found many instances where small choices made by authors and journals could have an outsized influence on the discoverability and reusability of data. Promisingly, articles also showed consistency and creativity in data storage choices as well as a strong trend toward open access publishing. Our analysis underscores the need to think critically about data accessibility and usability as marine eDNA metabarcoding studies, and eDNA projects more broadly, continue to proliferate.
Topics: DNA, Environmental; Biodiversity; DNA Barcoding, Taxonomic
PubMed: 36992947
DOI: 10.7717/peerj.14993 -
Journal of Personalized Medicine Oct 2022Predicting tooth loss is a persistent clinical challenge in the 21st century. While an emerging field in dentistry, computational solutions that employ machine learning... (Review)
Review
Predicting tooth loss is a persistent clinical challenge in the 21st century. While an emerging field in dentistry, computational solutions that employ machine learning are promising for enhancing clinical outcomes, including the chairside prognostication of tooth loss. We aimed to evaluate the risk of bias in prognostic prediction models of tooth loss that use machine learning. To do this, literature was searched in two electronic databases (MEDLINE via PubMed; Google Scholar) for studies that reported the accuracy or area under the curve (AUC) of prediction models. AUC measures the entire two-dimensional area underneath the entire receiver operating characteristic (ROC) curves. AUC provides an aggregate measure of performance across all possible classification thresholds. Although both development and validation were included in this review, studies that did not assess the accuracy or validation of boosting models (AdaBoosting, Gradient-boosting decision tree, XGBoost, LightGBM, CatBoost) were excluded. Five studies met criteria for inclusion and revealed high accuracy; however, models displayed a high risk of bias. Importantly, patient-level assessments combined with socioeconomic predictors performed better than clinical predictors alone. While there are current limitations, machine-learning-assisted models for tooth loss may enhance prognostication accuracy in combination with clinical and patient metadata in the future.
PubMed: 36294820
DOI: 10.3390/jpm12101682 -
BMC Medical Informatics and Decision... Jun 2021Natural language processing (NLP) has a significant role in advancing healthcare and has been found to be key in extracting structured information from radiology...
BACKGROUND
Natural language processing (NLP) has a significant role in advancing healthcare and has been found to be key in extracting structured information from radiology reports. Understanding recent developments in NLP application to radiology is of significance but recent reviews on this are limited. This study systematically assesses and quantifies recent literature in NLP applied to radiology reports.
METHODS
We conduct an automated literature search yielding 4836 results using automated filtering, metadata enriching steps and citation search combined with manual review. Our analysis is based on 21 variables including radiology characteristics, NLP methodology, performance, study, and clinical application characteristics.
RESULTS
We present a comprehensive analysis of the 164 publications retrieved with publications in 2019 almost triple those in 2015. Each publication is categorised into one of 6 clinical application categories. Deep learning use increases in the period but conventional machine learning approaches are still prevalent. Deep learning remains challenged when data is scarce and there is little evidence of adoption into clinical practice. Despite 17% of studies reporting greater than 0.85 F1 scores, it is hard to comparatively evaluate these approaches given that most of them use different datasets. Only 14 studies made their data and 15 their code available with 10 externally validating results.
CONCLUSIONS
Automated understanding of clinical narratives of the radiology reports has the potential to enhance the healthcare process and we show that research in this field continues to grow. Reproducibility and explainability of models are important if the domain is to move applications into clinical use. More could be done to share code enabling validation of methods on different institutional data and to reduce heterogeneity in reporting of study properties allowing inter-study comparisons. Our results have significance for researchers in the field providing a systematic synthesis of existing work to build on, identify gaps, opportunities for collaboration and avoid duplication.
Topics: Humans; Machine Learning; Natural Language Processing; Radiology; Radiology Information Systems; Reproducibility of Results
PubMed: 34082729
DOI: 10.1186/s12911-021-01533-7 -
Virulence Dec 2021is an emerging zoonotic pathogen. Over 100 putative virulence factors have been described, but it is unclear to what extent these virulence factors could contribute to... (Meta-Analysis)
Meta-Analysis
is an emerging zoonotic pathogen. Over 100 putative virulence factors have been described, but it is unclear to what extent these virulence factors could contribute to zoonotic potential of . We identified all virulence factors studied in experimental models of human origin in a systematic review and assessed their contribution to zoonotic potential in a subsequent genomic meta-analysis. PubMed and Scopus were searched for English-language articles that studied virulence published until 31 March 2021. Articles that analyzed a virulence factor by knockout mutation, purified protein, and/or recombinant protein in a model of human origin, were included. Data on virulence factor, strain characteristics, used human models and experimental outcomes were extracted. All publicly available genomes with available metadata on host, disease status and country of origin, were included in a genomic meta-analysis. We calculated the ratio of the prevalence of each virulence factor in human and pig isolates. We included 130 articles and 1703 genomes in the analysis. We identified 53 putative virulence factors that were encoded by genes which are part of the core genome and 26 factors that were at least twice as prevalent in human isolates as in pig isolates. Hhly3 and NisK/R were particularly enriched in human isolates, after stratification by genetic lineage and country of isolation. This systematic review and genomic meta-analysis have identified virulence factors that are likely to contribute to the zoonotic potential of .
Topics: Animals; Genomics; Streptococcal Infections; Streptococcus suis; Swine; Swine Diseases; Virulence; Virulence Factors
PubMed: 34666617
DOI: 10.1080/21505594.2021.1985760 -
Journal of Family Medicine and Primary... Mar 2020Common Data Elements (CDEs) are data-metadata descriptors used to collect research study data. CDEs facilitate the collection, processing, and sharing of breast cancer... (Review)
Review
BACKGROUND
Common Data Elements (CDEs) are data-metadata descriptors used to collect research study data. CDEs facilitate the collection, processing, and sharing of breast cancer data. This study intended to explore the CDEs of breast cancer for research databases and primary care systems.
METHODS
This study was conducted using systematic search and review. This systematic literature review covered PubMed, Scopus, Science Direct, SID, ISC, Web of Science, and Google Scholar search engine. It included studies in English language with accessible full-text from the beginning of 2007 to September 2019.
RESULTS
Reviewing 25 studies revealed that 52 percent of studies were carried out in the US and most studies were conducted between 2013 and 2015. The most domains for using CDEs were: Pathology Report and Registry. The CDEs of breast cancer for research databases were categorized into three categories namely clinical, research, and non-clinical and indicate the importance of these data elements. Most of the studies focused on creating and deploying clinical CDEs as physical examination, clinical history and pathology data.
CONCLUSION
The integration of biomedical and clinical data relevant to breast cancer enhances the power of research variable analysis and statistical analysis, thereby facilitating improved knowledge of effective therapeutic interventions. Also CDEs used to collect, store, and retrieve patient data in various health setting such as primary care and research databases.
PubMed: 32509607
DOI: 10.4103/jfmpc.jfmpc_931_19 -
International Journal of Qualitative... 2014To synthesize and interpret qualitative research findings focusing on parental experiences of skin-to-skin care (SSC) for newborn infants. (Meta-Analysis)
Meta-Analysis Review
AIM
To synthesize and interpret qualitative research findings focusing on parental experiences of skin-to-skin care (SSC) for newborn infants.
BACKGROUND
SSC induces many benefits for newborn infants and their parents. Three meta-analyses have been conducted on physiological outcomes, but no previous qualitative meta-synthesis on parental experiences of SSC has been identified.
DESIGN
The present meta-synthesis was guided by the methodology described by Paterson and co-workers.
DATA SOURCES
Four databases were searched, without year or language limitations, up until December 2013. Manual searches were also performed. The searches and subsequent quality appraisal resulted in the inclusion of 29 original qualitative papers from 9 countries, reporting experiences from 401 mothers and 94 fathers.
REVIEW METHODS
The meta-synthesis entails a meta-data analysis, analysis of meta-method, and meta-theory in the included primary studies. Based on the three analyses, the meta-synthesis represents a new interpretation of a phenomenon. The results of the meta-data analysis have been presented as a qualitative systematic review in a separate paper.
RESULTS
When synthesizing and interpreting the findings from the included analyses, a theoretical model of Becoming a parent under unfamiliar circumstances emerged. Providing SSC seems to be a restorative as well as an energy-draining experience. A supportive environment has been described as facilitating the restorative experience, whereas obstacles in the environment seem to make the provision of SSC energy-draining for parents. When the process is experienced as positive, it facilitates the growth of parental self-esteem and makes the parents ready to assume full responsibility for their child.
CONCLUSION
The results show that SSC can be interpreted not only as a family-including and important health care intervention but also in terms of actually becoming a parent. The process of becoming a parent in this specific situation is influenced by external factors in three different levels; family and friends, community, and society at large. The descriptions of providing SSC are similar to what has previously been described as the natural process of becoming a mother or a father.
Topics: Humans; Kangaroo-Mother Care Method; Mother-Child Relations; Object Attachment; Parents; Qualitative Research; Touch
PubMed: 25319747
DOI: 10.3402/qhw.v9.24907 -
Heliyon Aug 2023This study aims to comprehensively review the literature on human resource outsourcing (HRO) published from 2001 to 2021. The study begins with metadata analysis on 69... (Review)
Review
This study aims to comprehensively review the literature on human resource outsourcing (HRO) published from 2001 to 2021. The study begins with metadata analysis on 69 papers and presents insights into 32 papers on HRO identified from the Scopus and ISI Web of Science databases. The literature is classified based on content analysis, which comprises conceptual understanding, drivers and barriers, functions outsourced, and firm performance. The study reveals that cost advantage, organisational learning, and the opportunity to concentrate on core business functions motivate the organisation to practice HRO. However, the lack of psychological contact among current employees, the risk of opportunism in the freelancing organisation, lack of management legislation, and prior experience are the common barriers to HRO adoption. Despite thesedrawbacks and barriers, recruitment, payroll processing, and technology-centric human resource (HR) activities are standard HR functions outsourced by organisations. The contributions of this study are to offer an integrated and conclusive definition of HRO and provide a simple, easy-to-understand, yet comprehensive framework for understanding HRO practices in any organisation. Researchers and academicians can utilize this paper to explore future research directions while gaining a thorough understanding of the HRO concept.
PubMed: 37600375
DOI: 10.1016/j.heliyon.2023.e19018 -
Value in Health : the Journal of the... Mar 2023Real-world evidence (RWE) studies are increasingly being used to support healthcare decisions. Various frameworks, tools, and checklists exist for ensuring quality of... (Review)
Review
Use of Structured Template and Reporting Tool for Real-World Evidence for Critical Appraisal of the Quality of Reporting of Real-World Evidence Studies: A Systematic Review.
OBJECTIVES
Real-world evidence (RWE) studies are increasingly being used to support healthcare decisions. Various frameworks, tools, and checklists exist for ensuring quality of real-world data, designing robust studies, and assessing potential for bias. In January 2021, Structured Template and Reporting Tool for RWE (STaRT-RWE) was released to further reduce ambiguity, assumptions, and misinterpretation while planning, implementing, and reporting RWE studies of the safety and effectiveness of treatments. The objective of this study was to identify gaps in the reporting quality of published RWE studies by using this template for critical appraisal.
METHODS
Two reviewers conducted a keyword search on PubMed for free-full-text research articles using real-world data, RWE design, and safety with or without effectiveness outcomes of a medicinal product or intervention in humans of any age or gender, published in English between January 13, 2021, and January 13, 2022. Assessment of risk of bias was done using Assessment of Real-World Observational Studies critical appraisal tool. Deficiencies in methods and findings as per STaRT-RWE template were reported as frequencies.
RESULTS
A total of 54 of 2374 retrieved studies were included in the review. Based on the STaRT-RWE template, the studies inadequately reported empirically defined covariates, power and sample size calculation, attrition, sensitivity analyses, index date (day 0) defining criterion, predefined covariates, outcome, metadata about data source and software, objective, inclusion and exclusion criteria, analysis specifications, and follow-up.
CONCLUSIONS
The use of STaRT-RWE template along with its tables, design diagram, and library of published studies has a potential of improving robustness of RWE studies.
Topics: Humans; Bias; Checklist
PubMed: 36210293
DOI: 10.1016/j.jval.2022.09.003 -
PloS One 2023The use of cannabis for medicinal purposes has increased globally over the past decade since patient access to medicinal cannabis has been legislated across...
The use of cannabis for medicinal purposes has increased globally over the past decade since patient access to medicinal cannabis has been legislated across jurisdictions in Europe, the United Kingdom, the United States, Canada, and Australia. Yet, evidence relating to the effect of medical cannabis on the management of symptoms for a suite of conditions is only just emerging. Although there is considerable engagement from many stakeholders to add to the evidence base through randomized controlled trials, many gaps in the literature remain. Data from real-world and patient reported sources can provide opportunities to address this evidence deficit. This real-world data can be captured from a variety of sources such as found in routinely collected health care and health services records that include but are not limited to patient generated data from medical, administrative and claims data, patient reported data from surveys, wearable trackers, patient registries, and social media. In this systematic scoping review, we seek to understand the utility of online user generated text into the use of cannabis as a medicine. In this scoping review, we aimed to systematically search published literature to examine the extent, range, and nature of research that utilises user-generated content to examine to cannabis as a medicine. The objective of this methodological review is to synthesise primary research that uses social media discourse and internet search engine queries to answer the following questions: (i) In what way, is online user-generated text used as a data source in the investigation of cannabis as a medicine? (ii) What are the aims, data sources, methods, and research themes of studies using online user-generated text to discuss the medicinal use of cannabis. We conducted a manual search of primary research studies which used online user-generated text as a data source using the MEDLINE, Embase, Web of Science, and Scopus databases in October 2022. Editorials, letters, commentaries, surveys, protocols, and book chapters were excluded from the review. Forty-two studies were included in this review, twenty-two studies used manually labelled data, four studies used existing meta-data (Google trends/geo-location data), two studies used data that was manually coded using crowdsourcing services, and two used automated coding supplied by a social media analytics company, fifteen used computational methods for annotating data. Our review reflects a growing interest in the use of user-generated content for public health surveillance. It also demonstrates the need for the development of a systematic approach for evaluating the quality of social media studies and highlights the utility of automatic processing and computational methods (machine learning technologies) for large social media datasets. This systematic scoping review has shown that user-generated content as a data source for studying cannabis as a medicine provides another means to understand how cannabis is perceived and used in the community. As such, it provides another potential 'tool' with which to engage in pharmacovigilance of, not only cannabis as a medicine, but also other novel therapeutics as they enter the market.
Topics: Humans; Social Media; Cannabis; Medicine; Delivery of Health Care; United Kingdom
PubMed: 36662832
DOI: 10.1371/journal.pone.0269143