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"Data reporting"
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Democracy's detectives : the economics of investigative journalism
Investigative reporting generates new information about important issues that someone is trying to keep secret. Impacts of this journalism can be high. Yet the costs of discovering and telling these stories may also be significant. Democracy's Detectives uses economic theories of information to explain both how institutions breakdown in predictable ways and how journalists find and reveal which programs, products, and people go astray. The book analyzes the market for investigative reporting by examining more than 12,000 prize competition entries from 1979 to 2010 in the annual awards contest of Investigative Reporters and Editors. The results show what these investigative works in the United States uncovered and their impacts, and how the investigations were conducted and financially supported. Case studies of several investigative series demonstrate that each dollar invested in a story can yield hundreds of dollars in policy benefits. Examining the work of a Pulitzer prize-winning reporter shows how a single journalist over four decades generated more than 150 investigations that led to changes, including the passage of thirty-one state laws. Many valuable accountability stories go untold because media outlets bear the costs of reporting while the benefits spillover onto those who don't read or watch these investigations. Computational journalism may improve the economics of investigative reporting in two ways: lowering the cost of finding stories through better use of data and algorithms, and telling stories in more personalized and engaging ways. While breakdowns in institutions are inevitable, the combination of computation and journalism offers an expanded set of people new ways to hold those in power accountable and serve as democracy's detectives.-- Provided by publisher
The STROBE guidelines
by
Cuschieri, Sarah
in
Bibliographies
,
Data reporting; epidemiology; observational studies; publishing; research design
,
Epidemiology
2019
An observational study is a type of epidemiological study design, which can take the form of a cohort, a case-control, or a cross-sectional study. When presenting observational studies in manuscripts, an author needs to ascertain a clear presentation of the work and provide the reader with appropriate information to enable critical appraisal of the research. The Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines were created to aid the author in ensuring high-quality presentation of the conducted observational study. The original articles publishing the STROBE guidelines together with their bibliographies were identified and thoroughly reviewed. These guidelines consist of 22 checklist items that the author needs to fulfil before submitting the manuscript to a journal. The STROBE guidelines were created to aid the authors in presenting their work and not to act as a validation tool for the conducted study or as a framework to conduct an observational study on. The authors complying with these guidelines are more likely to succeed in publishing their observational study work in a journal.
Journal Article
The CONSORT statement
2019
Randomized control trials (RCT's) are the gold standard in evaluating and efficiently translating research data into clinical practice. The CONSORT statement was conceptualized in order to help ascertain standardization and reproducibility of RCT's. The articles publishing the CONSORT 2010 statement along with their bibliographies were identified and thoroughly reviewed. The CONSORT statement is made up of a 25-item checklist that provides the author with a solid backbone around which to construct and present an RCT. It sets standards on the trial's design, analysis, and interpretation of the results.
Journal Article
Qualitative data : an introduction to coding and analysis
by
Silverstein, Louise B
,
Auerbach, Carl
in
Methodology
,
PSYCHOLOGY
,
Psychology -- Research -- Methodology
2003
Qualitative Data is meant for the novice researcher who needs guidance on what specifically to do when faced with a sea of information. It takes readers through the qualitative research process, beginning with an examination of the basic philosophy of qualitative research, and ending with planning and carrying out a qualitative research study. It provides an explicit, step-by-step procedure that will take the researcher from the raw text of interview data through data analysis and theory construction to the creation of a publishable work.
The volume provides actual examples based on the authors' own work, including two published pieces in the appendix, so that readers can follow examples for each step of the process, from the project's inception to its finished product. The volume also includes an appendix explaining how to implement these data analysis procedures using NVIVO, a qualitative data analysis program.
Disparity in the quality of COVID-19 data reporting across India
by
Vasudevan, Varun
,
Vasudevan, Siddarth A.
,
Sankar, Varsha
in
Accessibility
,
Accuracy
,
Biostatistics
2021
Background
Transparent and accessible reporting of COVID-19 data is critical for public health efforts. Each Indian state has its own mechanism for reporting COVID-19 data, and the quality of their reporting has not been systematically evaluated. We present a comprehensive assessment of the quality of COVID-19 data reporting done by the Indian state governments between 19 May and 1 June, 2020.
Methods
We designed a semi-quantitative framework with 45 indicators to assess the quality of COVID-19 data reporting. The framework captures four key aspects of public health data reporting – availability, accessibility, granularity, and privacy. We used this framework to calculate a COVID-19 Data Reporting Score (CDRS, ranging from 0–1) for each state.
Results
Our results indicate a large disparity in the quality of COVID-19 data reporting across India. CDRS varies from 0.61 (good) in Karnataka to 0.0 (poor) in Bihar and Uttar Pradesh, with a median value of 0.26. Ten states do not report data stratified by age, gender, comorbidities or districts. Only ten states provide trend graphics for COVID-19 data. In addition, we identify that Punjab and Chandigarh compromised the privacy of individuals under quarantine by publicly releasing their personally identifiable information. The CDRS is positively associated with the state’s sustainable development index for good health and well-being (Pearson correlation:
r
=0.630,
p
=0.0003).
Conclusions
Our assessment informs the public health efforts in India and serves as a guideline for pandemic data reporting. The disparity in CDRS highlights three important findings at the national, state, and individual level. At the national level, it shows the lack of a unified framework for reporting COVID-19 data in India, and highlights the need for a central agency to monitor or audit the quality of data reporting done by the states. Without a unified framework, it is difficult to aggregate the data from different states, gain insights, and coordinate an effective nationwide response to the pandemic. Moreover, it reflects the inadequacy in coordination or sharing of resources among the states. The disparate reporting score also reflects inequality in individual access to public health information and privacy protection based on the state of residence.
Journal Article
Standardizing statistics and data reporting in orthopaedic research
by
Mauffrey Cyril
,
Parry, Joshua A
,
Strage, Katya E
in
Clinical medicine
,
Hypotheses
,
Medical research
2021
As the demand for research within orthopaedic surgery continues to grow, it is important to emphasize appropriate data reporting. Insufficient statistical reporting confounds data interpretation and makes it difficult to compare results. Currently, there are no guidelines for reporting results within the orthopaedic literature. This article discusses the importance of appropriate data reporting and proposes guidelines for presenting orthopaedic data to highlight clinical relevance rather than statistical significance.
Journal Article
Prostate Cancer Detection with Multiparametric Magnetic Resonance Imaging: Prostate Imaging Reporting and Data System Version 1 versus Version 2
2016
Background: Prostate Imaging Reporting and Data System (PI-RADS) is a globally acceptable standardization for multiparametric magnetic resonance imaging (mp-MRI) in prostate cancer (PCa) diagnosis. The American College of Radiology revised the PI-RADS to address the limitations of version 1 in December 2014. This study aimed to determine whether the PI-RADS version 2 (PI-RADS v2) scoring system improves the diagnostic accuracy of mp-MRI of the prostate compared with PI-RADS v1.
Methods: This retrospective study was approved by the institutional review board. A total of 401 consecutive patients, with clinically suspicious PCa undergoing 3.0 T mp-MRI (T2-weighted imaging + diffusion-weighted imaging + DCE) before transrectal ultrasound-guided biopsy between June 2013 and July 2015, were included in the study. All patients were scored using the 5-point PI-RADS scoring system based on either PI-RADS v1 or v2. Receiver operating characteristics were calculated for statistical analysis. Sensitivity, specificity, and diagnostic accuracy were compared using McNemar′s test.
Results: PCa was present in 150 of 401 (37.41%) patients. When we pooled data from both peripheral zone (PZ) and transition zone (TZ), the areas under the curve were 0.889 for PI-RADS v1 and 0.942 for v2 (P = 0.0001). Maximal accuracy was achieved with a score threshold of 4. At this threshold, in the PZ, similar sensitivity, specificity, and accuracy were achieved with v1 and v2 (all P > 0.05). In the TZ, sensitivity was higher for v2 than for v1 (96.36% vs. 76.36%, P = 0.003), specificity was similar for v2 and v1 (90.24% vs. 84.15%, P = 0.227), and accuracy was higher for v2 than for v1 (92.70% vs. 81.02%, P = 0.002).
Conclusions: Both v1 and v2 showed good diagnostic performance for the detection of PCa. However, in the TZ, the performance was better with v2 than with v1.
Journal Article
Beyond the HIPAA Privacy Rule
by
Services, Board on Health Care
,
Policy, Board on Health Sciences
,
Medicine, Institute of
in
Access control
,
Health
,
Health Insurance Portability and Accountability Act of 1996
2009
In the realm of health care, privacy protections are needed to preserve patients' dignity and prevent possible harms. Ten years ago, to address these concerns as well as set guidelines for ethical health research, Congress called for a set of federal standards now known as the HIPAA Privacy Rule.
In its 2009 report, Beyond the HIPAA Privacy Rule: Enhancing Privacy, Improving Health Through Research, the Institute of Medicine's Committee on Health Research and the Privacy of Health Information concludes that the HIPAA Privacy Rule does not protect privacy as well as it should, and that it impedes important health research.
Research Methods for Memory Studies
2013
The first practical guide to research methods in memory studies. This book provides expert appraisals of a range of techniques and approaches in memory studies, and focuses on methods and methodology as a way to help bring unity and coherence to this new field of study.