Automated Author ProfileSara Piva
0000-0002-1716-3151
Sara Piva
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 2.3 (sum of 3 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Vivli is an independent, non-profit organization that has developed a global data-sharing and analytics platform to serve all elements of the international research community. Our mission is to promote, coordinate, and facilitate scientific sharing and reuse of clinical research data through the creation and implementation of a sustainable global data-sharing enterprise. The Vivli platform includes an independent data repository, in-depth search engine and a cloud-based, secure analytics platform.
Authors
- University of Pittsburgh ;
- Charity Patterson ;
- Gwen Sowa ;
- Sara Piva ;
- Nam Vo ;
- Kevin Bell ;
- William Anderst ;
- Gina McKernan ;
- Carol Greco ;
- Michael Schneider
The BEST Trial (Biomarkers for Evaluating Spine Treatments) is a NIAMS-sponsored clinical trial being conducted through the NIH HEAL Initiative's Back Pain Consortium (BACPAC) Research Program. The primary objective of this trial is to inform a precision medicine approach to the treatment of Chronic Low-Back Pain by estimating an algorithm for optimally assigning treatments based on an individual's phenotypic markers and response to treatment. Interventions being evaluated in this trial are: (1) enhanced self-care (ESC), (2) acceptance and commitment therapy (ACT), (3) evidence-based exercise and manual therapy (EBEM), and (4) duloxetine.
Authors
- University of North Carolina at Chapel Hill ;
- Kevin Anstrom ;
- Daniel Clauw ;
- Gwendolyn Sowa ;
- Matthew Mauck ;
- Jeannie Bailey ;
- Sarah Bagaason ;
- Kelly Barth ;
- Anna Batorsky ;
- Kevin Bell ;
- Jeffrey Borckardt ;
- Anton Bowden ;
- Amber Brooks ;
- Timothy Carey ;
- Joel Castellanos ;
- Andrea Chadwick ;
- Lucy Chen ;
- Brooke Chidgey ;
- Diane Dalton ;
- Jonathan Dufour ;
- Aaron Fields ;
- Julie Fritz ;
- Rachel Goolsby ;
- Carol Greco ;
- Cameron Gunn ;
- Richard Harris ;
- Steven Harte ;
- Afton Hassett ;
- Anna Hoffmeyer ;
- Robert Hurley ;
- Anastasia Ivanova ;
- Sara Jones Berkeley ;
- Chelsea Kaplan ;
- Kelley Kidwell ;
- Gregory Knapik ;
- Michael Kosorok ;
- Gregorij Kurillo ;
- Remy Lobo ;
- Jeffrey Lotz ;
- Sean Mackey ;
- Prasath Mageswaran ;
- Sharmila Majumdar ;
- Jianren Mao ;
- William Marras ;
- Micah McCumber ;
- Samuel McLean ;
- Wolf Mehling ;
- Ulrike Mitchell ;
- Vitaly Napadow ;
- Conor O'Neill ;
- Kushang Patel ;
- Scott Peltier ;
- Sara Piva ;
- Matthew Psioda ;
- Bryce Rowland ;
- Sean Rundell ;
- Michael Schneider ;
- Andrew Schrepf ;
- John Sperger ;
- Nam Vo ;
- Mark Wallace ;
- Ajay Wasan ;
- Tristan Weaver ;
- Kenneth Weber ;
- David Williams ;
- Leslie Wilson ;
- Fadel Zeidan ;
- Beibo Zhao
The BEST Trial (Biomarkers for Evaluating Spine Treatments) is a NIAMS-sponsored clinical trial being conducted through the NIH HEAL Initiative's Back Pain Consortium (BACPAC) Research Program. The primary objective of this trial is to inform a precision medicine approach to the treatment of Chronic Low-Back Pain by estimating an algorithm for optimally assigning treatments based on an individual's phenotypic markers and response to treatment. Interventions being evaluated in this trial are: (1) enhanced self-care (ESC), (2) acceptance and commitment therapy (ACT), (3) evidence-based exercise and manual therapy (EBEM), and (4) duloxetine.
Authors
- University of North Carolina at Chapel Hill ;
- Kevin Anstrom ;
- Daniel Clauw ;
- Gwendolyn Sowa ;
- Matthew Mauck ;
- Jeannie Bailey ;
- Sarah Bagaason ;
- Kelly Barth ;
- Anna Batorsky ;
- Kevin Bell ;
- Jeffrey Borckardt ;
- Anton Bowden ;
- Amber Brooks ;
- Timothy Carey ;
- Joel Castellanos ;
- Andrea Chadwick ;
- Lucy Chen ;
- Brooke Chidgey ;
- Diane Dalton ;
- Jonathan Dufour ;
- Aaron Fields ;
- Julie Fritz ;
- Rachel Goolsby ;
- Carol Greco ;
- Cameron Gunn ;
- Richard Harris ;
- Steven Harte ;
- Afton Hassett ;
- Anna Hoffmeyer ;
- Robert Hurley ;
- Anastasia Ivanova ;
- Sara Jones Berkeley ;
- Chelsea Kaplan ;
- Kelley Kidwell ;
- Gregory Knapik ;
- Michael Kosorok ;
- Gregorij Kurillo ;
- Remy Lobo ;
- Jeffrey Lotz ;
- Sean Mackey ;
- Prasath Mageswaran ;
- Sharmila Majumdar ;
- Jianren Mao ;
- William Marras ;
- Micah McCumber ;
- Samuel McLean ;
- Wolf Mehling ;
- Ulrike Mitchell ;
- Vitaly Napadow ;
- Conor O'Neill ;
- Kushang Patel ;
- Scott Peltier ;
- Sara Piva ;
- Matthew Psioda ;
- Bryce Rowland ;
- Sean Rundell ;
- Michael Schneider ;
- Andrew Schrepf ;
- John Sperger ;
- Nam Vo ;
- Mark Wallace ;
- Ajay Wasan ;
- Tristan Weaver ;
- Kenneth Weber ;
- David Williams ;
- Leslie Wilson ;
- Fadel Zeidan ;
- Beibo Zhao