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Every research applicant wants to be in the lead while competing for a grant. The larger grants, like R01, particularly require the preliminary data to stay in the competition. The grant proposals without preliminary research do not stand a chance except for those applying for smaller grants (R03). Acquiring accurate preliminary research information is what every research writer should strive for. Regrettably, several grant proposals are rejected every year based on the flaws observed in the preliminary data section. Many applicants are asked for revision and resubmission due to the errors pointed by the panel reviewers. This article will guide you on how to deal with these errors.

Purpose of Preliminary Results

Before constructing the preliminary data section, one must know the reason to construct this section. This section is important for the reviewers because:

  • It makes them familiar with the research ideas and techniques that you are proposing
  • It shows how you will be able to attain your aims and outcomes
  • It helps them estimate the time-frame of your proposed research and clarifies that your research objectives are well within your grasp
  • It gives the verification of sample collection methods
  • It exhibits your ability to carry out the proposed research idea in the minds of reviewers
  • It proves the accuracy, authenticity, and utility of your research in front of the panel reviewers

Common Mistakes Found in the Preliminary Data Section

This section is scrutinized by the panel of peer reviewers, and the potential flaws are noted. These errors are highlighted in the form of ‘criticism notes’ that are written in response to your proposal. Many writers commit mistakes that are very commonly found among the declined applications. You can easily avoid these errors if you are guided enough. So, the following sub-headings will point out the most popular mistakes regarding this section:

Providing All the Information

It is great to provide your preliminary research data, but overloading your application is not a wise approach. Sadly, the research writers state every detail regarding the preliminary research. They do not leave suspense for the reviewers regarding the progression of their research. The reviewers learn every detail from the start, and there is nothing new left for them to look forward to in the coming sections of the applications. Information regarding all the other sections is elaborated on it. This bores the reviewers, and they see no innovative thrillers in your research idea. Hence, they decline your proposal due to the lack of interesting spoilers that they often seek.

How to Rewrite?

Excessive elaboration makes your application dull for the grant reviewers. To correct this flaw, you have to follow these protocols:

  • Write down the main points that need elaboration on a notepad.
  • Elaborate each point in a single line with minimal words.
  • Focus on that part of the preliminary that shows the feasibility of your research concept. (Steven, 2012)
  • The selected vocabulary should be simple to comprehend.
  • Remove all the duplicated statements by choosing the one that best elaborates your point.
  • Avoid elaboration of the outcomes of your research and leave it as a spoiler for the aims section.
  • The experiments and the used study techniques should just be mentioned as a trailer without elaboration.

Quoting Data from Literature

The data obtained from the outside sources are prohibited in the preliminary data section. Heaps of the grant proposals are criticized by the reviewers due to the inclusion of information quoted from the literature databases to support their preliminary research. The interference from the foreign sources supporting research hypotheses lowers the value of your application instead of increasing it. Such type of information is only beneficial in the other sections. Usually, this point is neglected by the writers, and both inside and outside sources of information are mingled together, resulting in confusion and grant rejection.

How to Rewrite?

The preliminary data section is solely dedicated to the data obtained wholly from your preliminary research. Here you have to state that your research laboratory is big enough to obtain an enormous amount of preliminary data (Ronald, 2012). The ground rules for correcting this error are:

  • Only the directly extracted data from your preliminary research should be scripted in the preliminary research data section.
  • Show the data that is obtained from the research experimentations carried out by your research laboratory.
  • The data from your collaborators and mentors are specially required in the training grants which belong to the F and K series of the National Institutes of Health (NIH).

Perplexing Charts, Figures & Tables

As a grant writer, you can demonstrate your research data with the help of diagrams, tables, charts, and figures. However, the represented data should be easy to read and comprehend. In many grant applications, the information scripted in this section in the form of pictorial representations is either complex or difficult to read. This greatly disappoints the reviewers and forces them to ask the writers for resubmission after clarifying the complicated data shown through complex diagrams.

How to Rewrite?

Simplicity and clarity are the key features to represent an idea. Thus, to rectify this flaw, you have to keep these points in your mind while giving a diagrammatical representation of your data derived from your preliminary research:

  • Use simple and clear pictorial representations for your research data.
  • Avoid the diagrammatical illustrations having multiple points explained in it.
  • Divide the complicated figures into separate illustrations for easy comprehension.
  • The size of the diagram should neither be too small for the readers nor too big as to cover the entire descriptive space of this section.

Irrelevant Information Provision

This error is found in the majority of the sections of the declined grant applicants. The level of irrelevant data is at its peak in the preliminary data section of several applications. This has introduced the term called ‘fishing expedition’ by the reviewers in the criticism notes. Fishing expedition means to search for the relevant knowledge in the sea of information provided by the grant writers. The provision of irrelevant data in this section tires the panel reviewers and compels them to reject the research application.

How to Rewrite?

To avoid this error, the writers should act as per these steps:

  • Gather all the information regarding your preliminary research on a notepad.
  • Categorize this data by evaluating which information directly concerns with your research aims, hypothesis, and outcomes.
  • Mention the directly related information in this section and set aside the remaining data for the research methodology section of your application.

Poor Flow between the Statements

Every section of your research should be scripted like a story for the reviewers with one event leading to another. The preliminary data section is no different. Now and then, we hear the criticism regarding the ambiguity and lack of correlation between statements in this section. When the statements are incoherent, it is difficult for the peer-reviewers to comprehend the meaning of the data derived from your preliminary research. This badly portrays your writing skills and harms your level of competency in the field of research, as well.

How to Rewrite?

This kind of error should be corrected by adhering to the following guidelines:

  • The script of your preliminary data section should mimic the rules of story writing.
  • Ensure that the present statement is coherent with the previous statement with the introduction of a new interesting event.
  • Each subsection of the preliminary research should be scripted as if the information of one subsection is generating further related information in the next subsection.

Missing Out the Supporting Data

The supporting information of your preliminary research section is related to the innovative designs, plans, and techniques that you will be explaining to prove the utility of your research idea. Various applications are deficient in the supportive data regarding their research idea every year. The writers do not either know the importance of introducing novel techniques through preliminary research or have enough dexterity to demonstrate the potential of newness in their proposed research idea. Hence, a lack of this type of supporting data urges the reviewers to reject the grant applications.

How to Rewrite?

This flaw can be removed from your application by keeping certain rules in your mind. These significant principles include:

  • The information you provide in the preliminary research section should be self-supportive.
  • Mention the innovative procedures that are used in your preliminary project as it is the key component. (Victoria, 2012)
  • Tell the reviewers about the novel data collected via your preliminary research and how it supports your research aims and hypothesis.
  • Show them through your preliminary research that how your laboratory equipment and the environment are all warmed up for your proposed research.

Biased Analysis of the Preliminary Data

The preliminary research data should not be biased. All researches are prone to imperfections and have their shortcomings. Applications with one-sided data favoring their research aims and outcomes are said to be artificial. These writers ignore the limitations of their preliminary research and only script those points that back their research idea. The level of objectivity is zero in such applications, which is very unrealistic. This makes the reviewers suspicious of the research idea that you are suggesting. Therefore, you are asked for a resubmission after adding the limitations of the preliminary research that you conducted.

How to Rewrite?

One-sided text can be altered according to the reviewers by following these instructions:

  • Write all the potential deficiencies in your preliminary research data.
  • Any missing data should also be mentioned after consultation from your statistician.
  • Then enumerate all the features that make your research a favorable one.
  • Now bend the research in your favor by finally justifying the enumerated features that back your research designs, equipment, and as well as your results.

Closure

The portion regarding the preliminary research data acts as the backbone of your grant proposal. It is a solid piece of evidence for the applicability and reliability of your proposed research concept. No research is perfect, but it should be good despite the limitations and objectivity that it offers. This perfection can only be attained by avoiding potential errors that can arise while loading your application with the preliminary data. This article can guide you even when you are asked for a resubmission after revising your errors. All the important guidelines for editing your errors in this section are exclusively provided here. You can easily benefit from them whenever needed.

References

  1. Houser, S.R. (2012, March). How to Obtain a National Heart, Lung, and Blood Institute-Sponsored K08 and K99/R00 Grant in the Current Funding Climate. Circulating Research, 110(7), 907–909. https://doi.org/10.1161/RES.0b013e3182539d49
  2. Vale, R.D. (2012, September). Evaluating How We Evaluate. Molecular Biology of the Cell23(17), 3285–3289. https://doi.org/10.1091/mbc.E12-06-0490
  3. McGovern, V.P. (2012, January). Getting Grants. Virulence3(1), 1–11. https://doi.org/10.4161/viru.3.1.18844
  4. Couch, M.E., Liu, J.C., Pynnonen, M.A., Rosenthal, E.L., Schmalbach, C.E., St John, M. (2016, February). Grant-writing pearls and pitfalls: maximizing funding opportunities. Otolaryngol Head Neck Surg, 154(2), 226–232. http://dx.doi.org/ 1177/0194599815620174
  5. Myers, N., Riley, H., & Wisdom, J.P. (2015, December). Recommendations for writing successful grant proposals: an information synthesis. Acad Med, 90(12), 1720–1725.
  6. http://dx.doi.org/10.1097/ACM.0000000000000811
  7. Barrowclough, O.J., & Hjelmervik, J.M. (2016, May) Interactive exploration of big scientific data: new representations and techniques. IEEE Comput Graph Appl, 36(3), 6–9. http://dx.doi.org/10.1109/MCG.2016.53

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