Counter-Predictive Research Outcomes.

1981 ◽  
Vol 10 (4) ◽  
pp. 556
Author(s):  
Marc Howard Ross ◽  
Jean I. Martin
Keyword(s):  
Research Outcomes ◽  
Predictive Research

Research outcomes following uterus transplantation at Royal Prince Alfred Hospital

2020 ◽  
Vol 29 (3) ◽  
Author(s):  
Dana Georgevsky ◽  
Ying Li ◽  
Kate Wyburn ◽  
Selvan Pather ◽  
Trevor TejadaBerges ◽  
...  
Keyword(s):  
Uterus Transplantation ◽  
Royal Prince Alfred Hospital ◽  
Research Outcomes ◽  
Alfred Hospital

Preregistration: Comparing Dream to Reality

2019 ◽  
Author(s):  
Aline Claesen ◽  
Sara Lucia Brazuna Tavares Gomes ◽  
francis tuerlinckx ◽  
wolf vanpaemel
Keyword(s):  
Research Finding ◽  
Third Party ◽  
Good Practices ◽  
Psychological Science ◽  
Research Outcomes

Doing research inevitably involves making numerous decisions that can influence research outcomes in such a way that it leads to overconfidence in statistical conclusions. One proposed method to increase the interpretability of a research finding is preregistration, which involves documenting analytic choices on a public, third-party repository prior to any influence by data. To investigate whether, in psychology, preregistration lives up to that potential, we focused on all articles published in Psychological Science with a preregistered badge between February 2015 and November 2017, and assessed the adherence to their corresponding preregistration plans. We observed deviations from the plan in all studies, and, more importantly, in all but one study, at least one of these deviations was not fully disclosed. We discuss examples and possible explanations, and highlight good practices for preregistering research.

Online, Asynchronous Data Collection in Qualitative Research

2019 ◽  
pp. 442-467
Author(s):  
Tracy Spencer ◽  
Linnea Rademaker ◽  
Peter Williams ◽  
Cynthia Loubier
Keyword(s):  
Qualitative Research ◽  
Data Collection ◽  
Face To Face ◽  
Research Outcomes ◽  
Data Collection Strategy ◽  
Time Distance ◽  
Privacy Issues

The authors discuss the use of online, asynchronous data collection in qualitative research. Online interviews can be a valuable way to increase access to marginalized participants, including those with time, distance, or privacy issues that prevent them from participating in face-to-face interviews. The resulting greater participant pool can increase the rigor and validity of research outcomes. The authors also address issues with conducting in-depth asynchronous interviews such as are needed in phenomenology. Advice from the field is provided for rigorous implementation of this data collection strategy. The authors include extensive excerpts from two studies using online, asynchronous data collection.

scholarly journals Investigator Initiated Clinical Trials (IICTs): A Systematic Search in Registries to Compare the Czech Republic and Portugal in Terms of Funding Policies and Scientific Outcomes

2021 ◽  
Author(s):  
C. Madeira ◽  
L. Hořavová ◽  
F. dos Santos ◽  
J. R. Batuca ◽  
K. Nebeska ◽  
...  
Keyword(s):  
Clinical Trials ◽  
Czech Republic ◽  
Clinical Research ◽  
Systematic Search ◽  
European Countries ◽  
The Czech Republic ◽  
Research Outcomes ◽  
Funding Policies ◽  
Funding Agencies ◽  
First Time

Abstract Objectives Clinical trials provide one of the highest levels of evidence to support medical practice. Investigator initiated clinical trials (IICTs) answer relevant questions in clinical practice that may not be addressed by industry. For the first time, two European Countries are compared in terms of IICTs, respective funders and publications, envisaging to inspire others to use similar indicators to assess clinical research outcomes. Methods A retrospective systematic search of registered IICTs from 2004 to 2017, using four clinical trials registries was carried out in two European countries with similar population, GDP, HDI and medical schools but with different governmental models to fund clinical research. Each IICT was screened for sponsors, funders, type of intervention and associated publications, once completed. Results IICTs involving the Czech Republic and Portugal were n = 439 (42% with hospitals as sponsors) and n = 328 (47% with universities as sponsors), respectively. The Czech Republic and Portuguese funding agencies supported respectively 61 and 27 IICTs. Among these, trials with medicinal products represent 52% in Czech Republic and 4% in Portugal. In the first, a higher percentage of IICTs’ publications in high impact factor journals with national investigators as authors was observed, when compared to Portugal (75% vs 15%). Conclusion The better performance in clinical research by Czech Republic might be related to the existence of specific and periodic funding for clinical research, although further data are still needed to confirm this relationship. In upcoming years, the indicators used herein might be useful to tracking clinical research outcomes in these and other European countries.

scholarly journals Protocol for establishing an Adaptive Diseases control Expert Programme in Tanzania (ADEPT) for integrating care of communicable and non-communicable diseases using tuberculosis and diabetes as a case study

BMJ Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. e041521
Author(s):  
Stellah G Mpagama ◽  
Kaushik Ramaiya ◽  
Troels Lillebæk ◽  
Blandina T Mmbaga ◽  
Marion Sumari-de Boer ◽  
...  
Keyword(s):  
Operational Research ◽  
Communicable Diseases ◽  
Health Facilities ◽  
Learning System ◽  
Management Approach ◽  
African Countries ◽  
Non Communicable Diseases ◽  
Research Outcomes ◽  
The Government

IntroductionMost sub-Saharan African countries endure a high burden of communicable infections but also face a rise of non-communicable diseases (NCDs). Interventions targeting particular epidemics are often executed within vertical programmes. We establish an Adaptive Diseases control Expert Programme in Tanzania (ADEPT) model with three domains; stepwise training approach, integration of communicable and NCDs and a learning system. The model aims to shift traditional vertical programmes to an adaptive diseases management approach through integrating communicable and NCDs using the tuberculosis (TB) and diabetes mellitus (DM) dual epidemic as a case study. We aim to describe the ADEPT protocol with underpinned implementation and operational research on TB/DM.Methods and analysisThe model implement a collaborative TB and DM services protocol as endorsed by WHO in Tanzania. Evaluation of the process and outcomes will follow the logic framework. A mixed research design with both qualitative and quantitative approaches will be used in applied research action. Anticipated implementation research outcomes include at the health facilities level for organising TB/DM services, pathways of patients with TB/DM seeking care in different health facilities, factors in service delivery that need deimplementation and the ADEPT model implementation feasibility, acceptability and fidelity. Expected operational research outcomes include additional identified patients with dual TB/DM, the prevalence of comorbidities like hypertension in patients with TB/DM and final treatment outcomes of TB/DM including treatment-related complications. Findings will inform the future policies and practices for integrating communicable and NCDs services.Ethics and disseminationEthical approval was granted by The National Research Health Ethical Committee (Ref-No. NIMR/HQ/R.8a/Vol.IX/2988) and the implementation endorsed by the government authorities. Findings will be proactively disseminated through multiple mechanisms including peer-reviewed journals, and engagement with various stakeholders’ example in conferences and social media.

Research on the strategy of intelligent analysis to improve sports person psychological experience in the era of artificial intelligence

2021 ◽  
pp. 1-11
Author(s):  
Lei Wu ◽  
Juan Wang ◽  
Long Jin ◽  
P. Hemalatha ◽  
R Premalatha
Keyword(s):  
Artificial Intelligence ◽  
Vital Role ◽  
Performance Ratio ◽  
Psychological Experience ◽  
The Public ◽  
Usable Knowledge ◽  
Intelligent Analysis ◽  
Accuracy Ratio ◽  
Depression Level ◽  
Predictive Research

Artificial intelligence (AI) is an excellent potential technology that is evolving day-to-day and a critical avenue for exploration in the world of computer science & engineering. Owing to the vast volume of data and the eventual need to turn this data into usable knowledge and realistic solutions, artificial intelligence approaches and methods have gained substantial prominence in the knowledge economy and community world in general. AI revolutionizes and raises athletics to an entirely different level. Although it is clear that analytics and predictive research have long played a vital role in sports, AI has a massive effect on how games are played, structured, and engaged by the public. Apart from these, AI helps to analyze the mental stability of the athletes. This research proposes the Artificial Intelligence assisted Effective Monitoring System (AIEMS) for the specific intelligent analysis of sports people’s psychological experience. The comparative analysis suggests the best AI strategies for analyzing mental stability using different criteria and resource factors. It is observed that the growth in the present incarnation indicates a promising future concerning AI use in elite athletes. The study ends with the predictive efficiency of particular AI approaches and procedures for further predictive analysis focused on retrospective methods. The experimental results show that the proposed AIEMS model enhances the athlete performance ratio of 98.8%, emotion state prediction of 95.7%, accuracy ratio of 97.3%, perception level of 98.1%, and reduces the anxiety and depression level of 15.4% compared to other existing models.

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