Ten Fatal Flaws of NIH
Grant Submissions
(and how to avoid them)
Steffanie A. Strathdee, PhD
Thomas L. Patterson, PhD
Disclaimers
• These points reflect the opinion of a few seasoned
NIH-funded researchers who are also chartered
reviewers; but are admittedly somewhat subjective
• Most refer to applications aimed at social,
behavioral and epidemiologic topics
• Points do not include scientific misconduct
• Points in italics reflect actual quotes that we have
received in our own summary statements , and
those we have written in reviews of others’
applications
10) Waiting Until the Last Minute
• Goal: Drafts should be circulated
to coauthors at least a few weeks
before the deadline
• Consequences:
−No time for feedback
−Typos, details can lack consistency
−Grant lacks polish, fabric, crossreferencing, and appearance of a ‘single
voice’
9) Wrong Funding Mechanism
• Goal:
– Communicate with funders to determine agency
interest and appropriate funding mechanism
– For an R01, present preliminary data to demonstrate
feasibility (especially for a trial)
– If lacking, consider other mechanisms, such as R21,
R03 or R34.
• Consequences:
– Feasibility questioned
– Study appears premature
– Often considered to be a fatal flaw
What do
they want?
8) Human Subjects Concern
• Goal: To ensure safety of subjects and staff,
addressing ‘4 points’, upholding equipoise in the
case of RCTs
• Consequences:
– Actual or perceived human subjects violation
– Infers inexperience and/or disregard for ethical
scientific conduct
– Can be a fatal flaw
– If proposal receives a fundable score, NGA is not
awarded until HRPP removes Human Subjects
Concern
7) Weak Statistical Plan or Study Power
• Goal:
– Study design factors in sufficient power in real-world
situations (e.g. attrition, missing data, control for
confounders)
• Exception: pilot study
– Power and analysis sections shown for each aim and
hypothesis
– should link back to conceptual framework and
measures
– present alternative strategies
– Should include up to date statistical techniques and
software
7) Weak Statistical Plan or Study Power
• Consequences:
–Reviewers will question feasibility for
meeting aims, (‘believability factor’)
–PI appears inexperienced
–Often a fatal flaw
–Statistical plan appears to have been
‘written by someone else’, or ‘cookiecutter’, inferring inexperience or laziness
–Methods can appear passé
6) Lack of a Back-up Plan
• Goal: Present a logical, feasible plan for
alternate strategies in case experiment or
hypothesis is not borne out as hoped
• Success of one aim should not depend on the
success of another
• Consequences:
– Reviewers will consider this a fatal flaw
– Aims appear as a ‘house of cards’
5) Gaps in Expertise
• Goal:
– Every content area and method matched to at
least one investigator with relevant expertise
– Co-investigator % effort matches what is required
to meet the aims
– Consultants included (with letters of support) to
fill any gaps in expertise
• Consequences:
– Proposal appears overly ambitious
– Fatal flaw for a new PI
4) Proposal Poorly Organized
• Goal:
– Background/significance should be concise, present
both sides of controversies
– Write for the layman, not the expert
– Half the proposal should be dedicated to methods
• Consequences:
– Background is too long, no room for methods
– Lit review appears one-sided, biased
– Background too technical, reviewer is lost in jargon
– Methods lacking sufficient detail or appear overly
dense and hard to digest
3) Missing /Problematic Hypotheses or
Weak/Absent Conceptual Framework
• Goal:
– Aims should be linked to clear, testable
hypotheses for which the outcome is not already
well established
– Aims and hypotheses should map onto conceptual
framework, measures, power and analysis
3) Missing /Problematic Hypotheses or
Weak/Absent Conceptual Framework
Consequences:
– Application appears merely ‘descriptive’
– Hypotheses appear ‘pedestrian in nature’
– Research questions and design appear murky
– Study design ‘lacks focus’
– Power and statistical analysis section appears to
be ‘cookie cutter’ since they do not tie back to
hypotheses/framework.
2) Lack of Significance/Innovation
• Goal: Proposal deals with an important,
exciting topic re: public health and/or clinical
decision-making, or moves the field forward.
• Consequences:
- Reviewers will be bored, significance rating will significantly
hamper overall score
- Proposal has a hard time competing with others
- A beautifully designed study that has no real significance or
innovation will not be funded
“And now, for the #1 fatal flaw of
NIH grant submissions…”
1) Overly Ambitious
• Goal:
– Project is designed to be feasible within the time frame
– Aims support one coherent project, not 2 or more
– Provide enough detail for reviewers to understand novel
methods and measures
– Project generates preliminary data to guide future studies
1) Overly Ambitious
Consequences:
– Threatens the ‘believability factor’
– Budget may not realistically support the aims
– Makes PI appear inexperienced; possible fatal flaw
– Reviewers may propose cutting an entire aim or 2,
or may unscore the proposal after deciding they
‘cannot re-write it for the PI’
– If you are funded, you stand to risk not being able to
meet aims, which can risk your reputation
GOOD LUCK!