The National Institutes of
Health (NIH) convened a group of interdisciplinary scientists, the Accumulating
Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Working Group,
to lead this project. The ADOPT Working Group
is tasked with identifying an initial core set of high-priority measures that
when used consistently in studies can facilitate the identification of replicable
predictors or moderators of treatment response.
The ADOPT Working Group launched
this process by entering potential predictors and mediators into the
Grid-Enabled Measures (GEM) Database (https://www.gem-measures.org/). Because GEM was developed
to share the best measures for many topics (read about GEM), 4
workspaces were created to organize the ADOPT work:
As the next step in this process, the ADOPT Working Group needs your
input regarding the measures entered in GEM. GEM provides
an online venue for you and other scientists to provide feedback on the
potential measures by
·
providing additional information
about measures already entered in GEM,
·
rating and commenting on each entered
measure, such as on its quality, ease of administration, ease of completion,
and availability, and
·
entering additional measures into
GEM, with supporting information, for consideration.
Contributing to this effort is incredibly easy:
·
Login as a GEM user to enter
information or comment. If you have not
previously used GEM, you can register by clicking a link in the upper right
hand corner of the home page.
·
Proceed to any of the four ADOPT
workspaces by clicking on each above workspace
link
·
Select ‘measures’ along the
left-hand side of the screen. You will
then be able to comment on the measures entered in GEM or add new ones.
·
If you add a new measure but
are not sure which workspace is most appropriate, pick one and enter it.
More detailed instructions can
be found in the attached handout or you can contact us at [email protected].
We would appreciate your input through GEM by October 7, 2016. The ADOPT Working Group will
consider your input as it develops an initial list of measures to present at a
forum during Obesity Week (Friday, November 4, 2016 from 8-9:30 am; 15097:
Toward Optimizing Long-Term Obesity Treatment: Measuring Core Variables in
Adult Weight Loss Trials).
We hope that you will agree
that this is an important effort and will work with us to help the obesity
research community to obtain better data to optimize long-term obesity
treatment. This project won’t work without your input!
Sincerely,
Paul MacLean, Alex Rothman, Cay
Loria, Tanya Agurs-Collins, Susan Czajkowski, and Holly Nicastro on behalf of
the
Accumulating Data to Optimally Predict obesity Treatment (ADOPT)
Core Measures Working Group
Daniel H. Bessesen, MD
Kerri Boutelle, PhD
Molly Bray, PhD
Anita P. Courcoulas, MD, MPH,
FACS
Elissa Epel, PhD
Amy Gorin, PhD
Kevin D. Hall, PhD
Mark Hopkins, PhD, MSc, BSc
John M. Jakicic, PhD
Leslie A. Lytle, PhD
Paul S. MacLean, PhD
(Co-chair)
Tiffany M. Powell-Wiley MD,
MPH, FAHA
Naresh M. Punjabi, MD, PhD
Susan B. Roberts, PhD
Michael Rosenbaum, MD
Alex Rothman, PhD (Co-chair)
Donna H. Ryan, MD
Brian E. Saelens, PhD
Cary R. Savage, PhD
Dana M Small, PhD
Angelina R. Sutin, PhD
David M. Williams, PhD
Shannon N. Zenk, PhD, MPH, RN
NIH Planning Group
Tanya Agurs-Collins, PhD, R.D.
(Co-lead)
S. Sonia Arteaga, PhD
Rachel Ballard, MD, MPH
David Berrigan PhD MPH
Josephine Boyington, PhD, MPH,
CNS
Susan M. Czajkowski, PhD (Co-lead)
Janet M. de Jesus, MS, RD
Mary Evans, PhD
Paige A. Green, PhD, MPH
Christine M. Hunter, Ph.D.,
ABPP
Aaron D. Laposky, PhD
Maren R. Laughlin, PhD
Catherine (Cay) Loria, PhD,
MS, MA (Co-lead)
Padma Maruvada PhD
Richard P Moser, PhD
Holly Nicastro, PhD, MPH (Co-lead)
Lis Nielsen, PhD
Charlotte Pratt, PhD, MS, RD
Jill Reedy, PhD, MPH, RD
Elise Rice, PhD
Katrina J. Serrano, PhD, CHES
Luke E. Stoeckel, PhD
Aynur Unalp-Arida, MD, MSc,
PhD
Susan Z. Yanovski, MD
Deborah Young-Hyman, PhD.