Mapping evidence of food safety at transport stations in Africa: a scoping review protocol

IntroductionIn Africa, travels, urbanisation and changing consumer habits are increasing the number of people buying and eating food prepared/sold at public spaces including transport stations, particularly in the urban and periurban areas. Although food trading in such public spaces serves as a source of livelihood for many people, unsafe food can have a negative impact on health. We, therefore, aim to systematically explore and examine the literature, and describe the evidence on food safety (food handling, storage, preparation and sale, packaging of food when sold, hygiene of sale venue and quality (nutrition) of food sold/purchased/eaten) at transport stations to inform policy, as well as identify research gaps for future studies in Africa.Methods and analysisWe will employ the Arksey & O’Malley framework, Levac et al recommendations and the Joanna Briggs Institute guidelines to guide this study. We will conduct a comprehensive search in PubMed, SCOPUS, Web of Science, Google Scholar and EBSCOhost (Academic search complete, CINAHL with Full-text and Health Source) from inception to December 2019 for relevant peer-review articles using a combination of keywords/search terms with no limitations. We will also search for relevant literature from the reference list of all included articles. Two investigators will independently screen the articles in parallel at the abstract and full-text phases using the eligibility criteria as a guide. Data extraction will be done using a piloted data extraction form designed in a Microsoft Word tabular format. Afterward, the extracted data will be collated into themes and subthemes, summarised, and the results reported using a narrative approach. We will the Preferred Reporting Items for Systematic Reviews and Meta-analyses: Extension for scoping reviews checklist to report this study results.Ethics and disseminationEthics approval is not required. All sources of data will be adequately cited and added to the reference list. We will present the final scoping review results at the appropriate workshops, meetings, conferences, as well as submit for peer-review and publication in a scientific journal.

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Virtual reality in medical students’ education: a scoping review protocol

BMJ Open ◽

10.1136/bmjopen-2020-046986 ◽

2021 ◽

Vol 11 (5) ◽

pp. e046986

Author(s):

Jiang Haowen ◽

Sunitha Vimalesvaran ◽

Bhone Myint Kyaw ◽

Lorainne Tudor Car

Keyword(s):

Medical Education ◽

Virtual Reality ◽

Scoping Review ◽

Data Extraction ◽

Grey Literature ◽

Real Life ◽

Future Research ◽

Review Author ◽

Reference List ◽

Scoping Reviews

BackgroundVirtual reality (VR) is a technology that produces a virtual manifestation of the real world. In recent years, VR has been increasingly used as a tool in medical education. The use of VR in medical education has large potential, as it allows for distance learning and training which may be challenging to deliver in real life. VR encompasses different tools and applications. There is a need to explore how VR has been employed in medical education to date.ObjectiveThe objective of this scoping review is to conceptualise the VR tools available and the applications of VR in undergraduate medical education as reported in the literature. This scoping review will identify any gaps in this field and provide suggestions for future research.Methods and analysisThe relevant studies will be examined using the Joanna Briggs Institute methodological framework for scoping studies. A comprehensive search from a total of six electronic databases and grey literature sources will be performed. The reference list of included studies will be screened for additional studies. The screening and data extraction will be done in parallel and independently by two review authors. Any discrepancies will be resolved through consensus or discussion with a third review author. A data extraction form has been developed using key themes from the research questions. The extracted data will be qualitatively analysed and presented in a diagrammatic or tabular form, alongside a narrative summary, in line with Preferred Reporting Items for Systematic Reviews and Meta-Analysis: extension for Scoping Reviews reporting guidelines.Ethics and disseminationAll data will be collected from published and grey literature. Ethics approval is therefore not a requirement. We will present our findings at relevant conferences and submit them for publications in peer-reviewed journals.

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What motivates people to commence a graduate entry nursing programme: a mixed method scoping review

BMC Nursing ◽

10.1186/s12912-021-00564-9 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Rachel Macdiarmid ◽

Rosemary Turner ◽

Rhona Winnington ◽

Patricia McClunie-Trust ◽

Andrea Donaldson ◽

...

Keyword(s):

Nursing Education ◽

Scoping Review ◽

Mixed Method ◽

Data Extraction ◽

Financial Burden ◽

Reference List ◽

Mixed Method Research ◽

Graduate Entry ◽

Scoping Reviews ◽

Course Length

Abstract Background The global deficit of nurses demands urgent attention in the recruitment and education of this future workforce. Graduate entry nursing (GEN) programmes are one option for people with undergraduate degrees who are seeking nursing education. Determining the key motivations for enrolling in these programmes will support the development of new initiatives in the education sector to both recruit and retain this future workforce and inform future primary research. This scoping review aims to comprehensively describe what motivates graduates to enrol in GEN programmes. Methods Peer reviewed studies of quantitative, qualitative and mixed-method research investigating motivations to commence a graduate entry nursing programme were included, following a pre-determined protocol. Electronic databases searched included Cumulative Index to Nursing and Allied Health Literature (CINAHL), Emcare, ERIC, Medline and Scopus. Screening, data extraction and analysis was initially in duplicate and independent, then consensus reached. Qualitative and quantitative data was analysed and reported separately then combined thematically as a narrative synthesis in a convergent segregated approach. Reporting followed preferred reporting guidelines for scoping reviews. Results Of the 491 studies retrieved in July 2020, across the five databases and reference list search, six met the inclusion criteria. Four were qualitative studies, one mixed-methods, and one quantitative, respectively from Australia, USA, and New Zealand. Four themes of motivation were identified: 1) finding meaning and purpose through altruism and caring; 2) seeking a satisfying career, 3) looking for a change in direction and, 4) reduced financial burden due to course length and provision of scholarships. Conclusions There is a paucity of studies specifically seeking to investigate student motivations for enrolling in a GEN programme and only limited studies giving insights into motivators for enrolling in a GEN programme, therefore this scoping review contributes new understandings on the reason’s students choose GEN programmes. These are both altruistic and practical and include personal desires to help others, the need to pursue a satisfying and meaningful career and the shorter period out of the workforce offered by an accelerated programme of study.

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Artificial Intelligence for Skin Cancer Detection: A Scoping Review (Preprint)

10.2196/preprints.22934 ◽

2020 ◽

Author(s):

Abdulrahman Takiddin ◽

Jens Schneider ◽

Yin Yang ◽

Alaa Abd-Alrazaq ◽

Mowafa Househ

Keyword(s):

Artificial Intelligence ◽

Skin Cancer ◽

Scoping Review ◽

Performance Metrics ◽

Data Extraction ◽

Characteristic Curve ◽

Evaluation Metrics ◽

Cancer Type ◽

Computer Algorithms ◽

Scoping Reviews

BACKGROUND Skin cancer is the most common cancer type affecting humans. Traditional skin cancer diagnosis methods are costly, require a professional physician, and take time. Hence, to aid in diagnosing skin cancer, Artificial Intelligence (AI) tools are being used, including shallow and deep machine learning-based techniques that are trained to detect and classify skin cancer using computer algorithms and deep neural networks. OBJECTIVE The aim of this study is to identify and group the different types of AI-based technologies used to detect and classify skin cancer. The study also examines the reliability of the selected papers by studying the correlation between the dataset size and number of diagnostic classes with the performance metrics used to evaluate the models. METHODS We conducted a systematic search for articles using IEEE Xplore, ACM DL, and Ovid MEDLINE databases following the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines. The study included in this scoping review had to fulfill several selection criteria; to be specifically about skin cancer, detecting or classifying skin cancer, and using AI technologies. Study selection and data extraction were conducted by two reviewers independently. Extracted data were synthesized narratively, where studies were grouped based on the diagnostic AI techniques and their evaluation metrics. RESULTS We retrieved 906 papers from the 3 databases, but 53 studies were eligible for this review. While shallow techniques were used in 14 studies, deep techniques were utilized in 39 studies. The studies used accuracy (n=43/53), the area under receiver operating characteristic curve (n=5/53), sensitivity (n=3/53), and F1-score (n=2/53) to assess the proposed models. Studies that use smaller datasets and fewer diagnostic classes tend to have higher reported accuracy scores. CONCLUSIONS The adaptation of AI in the medical field facilitates the diagnosis process of skin cancer. However, the reliability of most AI tools is questionable since small datasets or low numbers of diagnostic classes are used. In addition, a direct comparison between methods is hindered by a varied use of different evaluation metrics and image types.

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Instruments for measuring nursing research competence: a protocol for a scoping review

BMJ Open ◽

10.1136/bmjopen-2020-042325 ◽

2021 ◽

Vol 11 (2) ◽

pp. e042325

Author(s):

Qirong Chen ◽

Chongmei Huang ◽

Aimee R Castro ◽

Siyuan Tang

Keyword(s):

Scoping Review ◽

Data Extraction ◽

Target Population ◽

Measurement Properties ◽

Nursing Research ◽

Measurement Instruments ◽

Health Measurement ◽

Research Competence ◽

Scoping Reviews

IntroductionNursing research competence of nursing personnel has received much attention in recent years, as nursing has developed as both an independent academic discipline and an evidence-based practiing profession. Instruments for appraising nursing research competence are important, as they can be used to assess nursing research competence of the target population, showing changes of this variable over time and measuring the effectiveness of interventions for improving nursing research competence. There is a need to map the current state of the science of the instruments for nursing research competence, and to identify well validated and reliable instruments. This paper describes a protocol for a scoping review to identify, evaluate, compare and summarise the instruments designed to measure nursing research competence.Methods and analysisThe scoping review will be conducted following Arksey and O’Malley’s methodological framework and Levac et al’s additional recommendations for applying this framework. The scoping review will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. The protocol is registered through the Open Science Framework (https://osf.io/ksh43/). Eight English databases and two Chinese databases will be searched between 1 December 2020 and 31 December 2020 to retrieve manuscripts which include instrument(s) of nursing research competence. The literature screening and data extraction will be conducted by two researchers, independently. A third researcher will be involved when consensus is needed. The COnsensus-based Standards for the selection of health Measurement INstruments methodology will be used to evaluate the methodological quality of the included studies on measurement properties of the instruments, as well as the quality of all the instruments identified.Ethics and disseminationEthical approval is not needed. We will disseminate the findings through a conference focusing on nursing research competence and publication of the results in a peer-reviewed journal.

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Irritant-Induced Chronic Cough Triggers: A Scoping Review and Clinical Checklist

American Journal of Speech-Language Pathology ◽

10.1044/2021_ajslp-20-00362 ◽

2021 ◽

pp. 1-31

Author(s):

Mary J. Sandage ◽

Elizabeth S. Ostwalt ◽

Lauren H. Allison ◽

Grace M. Cutchin ◽

Mariah E. Morton ◽

...

Keyword(s):

Scoping Review ◽

Full Text ◽

Chronic Cough ◽

English Language ◽

Meta Analysis ◽

Occupational Exposures ◽

Unique Contribution ◽

International Scope ◽

Scoping Reviews ◽

Full Text Review

Purpose The primary aim of this review was to identify environmental irritants known to trigger chronic cough through the life span and develop a comprehensive clinically useful irritant checklist. Method A scoping review was conducted using the Preferred Reporting Items for Systematic Review and Meta-Analysis Extension for Scoping Reviews, checklist, and explanation. English-language, full-text resources were identified through Medline, PsycINFO, SPORTDiscus, Web of Science, and ProQuest Dissertations and Theses Global. Results A total of 1,072 sources were retrieved; of these, 109 were duplicates. Titles of abstracts of 963 articles were screened, with 295 selected for full-text review. Using the exclusion and inclusion criteria listed, 236 articles were considered eligible and 214 different triggers were identified. Triggers were identified from North America, Europe, Africa, Asia, and Australia. Occupational exposures were also delineated. Conclusions A clinically useful checklist of both frequently encountered triggers and idiosyncratic or rare triggers was developed. The clinical checklist provides a unique contribution to streamline and standardize clinical assessment of irritant-induced chronic cough. The international scope of this review extends the usefulness of the clinical checklist to clinicians on most continents.

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Diagnosing Overtraining Syndrome: A Scoping Review

Sports Health A Multidisciplinary Approach ◽

10.1177/19417381211044739 ◽

2021 ◽

pp. 194173812110447

Author(s):

Justin Carrard ◽

Anne-Catherine Rigort ◽

Christian Appenzeller-Herzog ◽

Flora Colledge ◽

Karsten Königstein ◽

...

Keyword(s):

Scoping Review ◽

Sports Medicine ◽

Female Athletes ◽

Data Extraction ◽

Eligibility Criteria ◽

Level Of Evidence ◽

Exercise Tests ◽

Overtraining Syndrome ◽

Scoping Reviews ◽

Study Characteristics

Context: Overtraining syndrome (OTS) is a condition characterized by a long-term performance decrement, which occurs after a persisting imbalance between training-related and nontraining-related load and recovery. Because of the lack of a gold standard diagnostic test, OTS remains a diagnosis of exclusion. Objective: To systematically review and map biomarkers and tools reported in the literature as potentially diagnostic for OTS. Data Sources: PubMed, Web of Science, and SPORTDiscus were searched from database inception to February 4, 2021, and results screened for eligibility. Backward and forward citation tracking on eligible records were used to complement results of database searching. Study Selection: Studies including athletes with a likely OTS diagnosis, as defined by the European College of Sport Science and the American College of Sports Medicine, and reporting at least 1 biomarker or tool potentially diagnostic for OTS were deemed eligible. Study Design: Scoping review following the guidelines of the Joanna Briggs Institute and PRISMA Extension for Scoping Reviews (PRISMA-ScR). Level of Evidence: Level 4. Data Extraction: Athletes’ population, criteria used to diagnose OTS, potentially diagnostic biomarkers and tools, as well as miscellaneous study characteristics were extracted. Results: The search yielded 5561 results, of which 39 met the eligibility criteria. Three diagnostic scores, namely the EROS-CLINICAL, EROS-SIMPLIFIED, and EROS-COMPLETE scores (EROS = Endocrine and Metabolic Responses on Overtraining Syndrome study), were identified. Additionally, basal hormone, neurotransmitter and other metabolite levels, hormonal responses to stimuli, psychological questionnaires, exercise tests, heart rate variability, electroencephalography, immunological and redox parameters, muscle structure, and body composition were reported as potentially diagnostic for OTS. Conclusion: Specific hormones, neurotransmitters, and metabolites, as well as psychological, electrocardiographic, electroencephalographic, and immunological patterns were identified as potentially diagnostic for OTS, reflecting its multisystemic nature. As exemplified by the EROS scores, combinations of these variables may be required to diagnose OTS. These scores must now be validated in larger samples and within female athletes.

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Rehabilitation Care at the Time of Coronavirus Disease-19 (COVID-19) Pandemic: A Scoping Review of Health System Recommendations

Frontiers in Aging Neuroscience ◽

10.3389/fnagi.2021.781271 ◽

2022 ◽

Vol 13 ◽

Author(s):

Ahmed M. Negm ◽

Adrian Salopek ◽

Mashal Zaide ◽

Victoria J. Meng ◽

Carlos Prada ◽

...

Keyword(s):

Scoping Review ◽

Full Text ◽

Data Extraction ◽

Health Care Systems ◽

Social Systems ◽

World Health ◽

Rehabilitation Services ◽

Rehabilitation Care ◽

The World ◽

Health Organization

Purpose: The coronavirus disease-19 (COVID-19) was declared a pandemic by the World Health Organization in March 2020. COVID-19, caused by SARS-CoV-2 has imposed a significant burden on health care systems, economies, and social systems in many countries around the world. The provision of rehabilitation services for persons with active COVID-19 infection poses challenges to maintaining a safe environment for patients and treating providers.Materials and Methods: Established frameworks were used to guide the scoping review methodology. Medline, Embase, Pubmed, CINAHL databases from inception to August 1, 2020, and prominent rehabilitation organizations’ websites were searched.Study Selection: We included articles and reports if they were focused on rehabilitation related recommendations for COVID-19 patients, treating providers, or the general population.Data Extraction: Pairs of team members used a pre-tested data abstraction form to extract data from included full-text articles. The strength and the quality of the extracted recommendations were evaluated by two reviewers using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach.Results: We retrieved 6,468 citations, of which 2,086 were eligible for review, after duplicates were removed. We excluded 1,980 citations based on title and abstract screening. Of the screened full-text articles, we included all 106 studies. A summary of recommendations is presented. We assessed the overall evidence to be strong and of fair quality.Conclusion: The rehabilitation setting, and processes, logistics, and patient and healthcare provider precaution recommendations identified aim to reduce the spread of SARS-CoV-2 infection and ensure adequate and safe rehabilitation services, whether face-to-face or through teleservices. The COVID-19 pandemic is rapidly changing. Further updates will be needed over time in order to incorporate emerging best evidence into rehabilitation guidelines.

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Clinical prediction models for hospital falls: a scoping review protocol

BMJ Open ◽

10.1136/bmjopen-2021-051047 ◽

2021 ◽

Vol 11 (9) ◽

pp. e051047

Author(s):

Rex Parsons ◽

Susanna M Cramb ◽

Steven M McPhail

Keyword(s):

Real Time ◽

Scoping Review ◽

Fall Risk ◽

Prediction Models ◽

Reporting Quality ◽

Reference List ◽

Fall Prediction ◽

Scoping Reviews ◽

Ethical Approval ◽

Meta Analyses

IntroductionFalls remain one of the most prevalent adverse events in hospitals and are associated with substantial negative health impacts and costs. Approaches to assess patients’ fall risk have been implemented in hospitals internationally, ranging from brief screening questions to multifactorial risk assessments and complex prediction models, despite a lack of clear evidence of effect in reducing falls in acute hospital environments. The increasing digitisation of hospital systems provides new opportunities to understand and predict falls using routinely recorded data, with potential to integrate fall prediction models into real-time or near-real-time computerised decision support for clinical teams seeking to mitigate fall risk. However, the use of non-traditional approaches to fall risk prediction, including machine learning using integrated electronic medical records, has not yet been reviewed relative to more traditional fall prediction models. This scoping review will summarise methodologies used to develop existing hospital fall prediction models, including reporting quality assessment.Methods and analysisThis scoping review will follow the Arksey and O’Malley framework and its recent advances, and will be reported using Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews recommendations. Four electronic databases (CINAHL via EBSCOhost, PubMed, IEEE Xplore and Embase) will be initially searched for studies up to 12 November 2020, and searches may be updated prior to final reporting. Additional studies will be identified by reference list review and citation analysis of included studies. No restriction will be placed on the date or language of identified studies. Screening of search results and extraction of data will be performed by two independent reviewers. Reporting quality will be assessed by the adherence to the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis.Ethics and disseminationEthical approval is not required for this study. Findings will be disseminated through peer-reviewed publication and scientific conferences.

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Artificial Intelligence in Predicting Cardiac Arrest: A Scoping Review (Preprint)

10.2196/preprints.30798 ◽

2021 ◽

Author(s):

Asma Alamgir ◽

Osama Mousa 2nd ◽

Zubair Shah 3rd

Keyword(s):

Artificial Intelligence ◽

At Risk ◽

Cardiac Arrest ◽

Scoping Review ◽

Pediatric Population ◽

Data Extraction ◽

Warning System ◽

Reference List ◽

Evaluation Tool ◽

Patients At Risk

BACKGROUND Cardiac arrest is a life-threatening cessation of heart activity. Early prediction of cardiac arrest is important as it provides an opportunity to take the necessary measures to prevent or intervene during the onset. Artificial intelligence technologies and big data have been increasingly used to enhance the ability to predict and prepare for the patients at risk. OBJECTIVE This study aims to explore the use of AI technology in predicting cardiac arrest as reported in the literature. METHODS Scoping review was conducted in line with guidelines of PRISMA Extension for Scoping Review (PRISMA-ScR). Scopus, Science Direct, Embase, IEEE, and Google Scholar were searched to identify relevant studies. Backward reference list checking of included studies was also conducted. The study selection and data extraction were conducted independently by two reviewers. Data extracted from the included studies were synthesized narratively. RESULTS Out of 697 citations retrieved, 41 studies were included in the review, and 6 were added after backward citation checking. The included studies reported the use of AI in the prediction of cardiac arrest. We were able to classify the approach taken by the studies in three different categories - 26 studies predicted cardiac arrest by analyzing specific parameters or variables of the patients while 16 studies developed an AI-based warning system. The rest of the 5 studies focused on distinguishing high-risk cardiac arrest patients from patients, not at risk. 2 studies focused on the pediatric population, and the rest focused on adults (n=45). The majority of the studies used datasets with a size of less than 10,000 (n=32). Machine learning models were the most prominent branch of AI used in the prediction of cardiac arrest in the studies (n=38) and the most used algorithm belonged to the neural network (n=23). K-Fold cross-validation was the most used algorithm evaluation tool reported in the studies (n=24). CONCLUSIONS : AI is extensively being used to predict cardiac arrest in different patient settings. Technology is expected to play an integral role in changing cardiac medicine for the better. There is a need for more reviews to learn the obstacles of implementing AI technologies in the clinical setting. Moreover, research focusing on how to best provide clinicians support to understand, adapt and implement the technology in their practice is also required.

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Mapping evidence on access to healthcare information by women of reproductive age in low-and-middle-income countries: scoping review protocol

Systematic Reviews ◽

10.1186/s13643-019-1203-5 ◽

2019 ◽

Vol 8 (1) ◽

Author(s):

Joyce T. Shatilwe ◽

Tivani P. Mashamba-Thompson

Keyword(s):

Scoping Review ◽

Full Text ◽

Grey Literature ◽

Relevant Literature ◽

Access To Healthcare ◽

Reproductive Age ◽

Future Research ◽

Reference List ◽

Women Of Reproductive Age ◽

Healthcare Information

Abstract Background Research shows that there are inadequate interventions in resource-limited settings that could enable women of reproductive age to access and use health services in those settings. The main objective of this scoping review is to map the evidence on access to healthcare information by women of reproductive age in LMICs. Method and analysis The primary search will include Google Scholar, Science Direct, PubMed, EBSCOhost (Academic search complete, CINAHL with full text, MEDLINE with full text, MEDLINE), Emerald, Embase, CDSR, PsycINFO, published and peer review journals, organisational projects, conference papers, reference list, grey literature sources, as well as reports related to this objective will be included in the study. Identified keywords will be used to search articles from the studies. The articles and abstracts will be screened by two independent reviewers (JS and TPMT). Inclusion and exclusion criteria will be considered to guide the screening. A thematic content analysis will be used to present the narrative account of the reviews, using NVivo computer software (version 11). Discussions The scoping review will focus on women of reproductive age in LMICs. We anticipate finding relevant literature on the interventions aimed at accessing health care services in LMICs. The study findings will help reveal research gaps to guide future research. Scoping review registration Not registered with PROSPERO (not needed). Protocol and registration This scoping review was not registered.

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