Guide to Conducting Meta-Analysis

Before knowing the systematic steps to meta-analysis, let us first know what it means by Meta-analysis.

What is a meta-analysis?

In simpler terms, meta-analysis is a quantitative study comparing the results of two or more different primary studies with conflicting results using a statistical procedure. It is used to establish a statistical significance.

Steps to meta-analysis:

There are four steps to conducting a meta-analysis.

  1. Framing a research question

The first step is to frame a clear and interesting question. As it is a quantitative study, the PICO framework is being used to formulate the question (where PICO stands for Population, Intervention, Control, and Outcomes).

  1. Searching the literature

After framing the question, the next step is to search all the databases to find a sample that is similar to our study. The most relevant way is to use a keyword search as it yields almost accurate results. Those results will help us to understand our topic much better.

Inclusion and Exclusion criteria

After finding out a list of studies, the researcher now decides which studies will be included and excluded from the process of meta-analysis.

  1. Choosing a meta-analytical method

There are four meta-analytical methods, three fixed-effect methods, and one random-effects method. Choosing the correct meta-analytical method should depend on the framed research question.

The three fixed-effect methods are

  • Mantel-Haenszel method – This test is also known as the Cochran–Mantel–Haenszel test (CMH) and is used in the analysis of stratified or matched categorical data.
  • Peto Method – This method can only be used to pool odd ratios. It is a sum of ‘O-E’ statistics where ‘O’ stands for the observed number of events and ‘E’ for the expected number of events.
  • Inverse Variance Method – In the inverse variance method, the weight given to each study is the inverse of the variance of the effect estimate.

The random-effects method is an assumption that the observed data can vary across studies.

  1. Finding out the result

The last step is to find out the results using one of the meta-analytical methods and report them.

While reporting the results, the researcher uses tables and figures that include all the information showing effect sizes, number of observations, errors, etc. Along with that, whatever data is present in the tables and figures should also be explained in the results or discussion section. The researcher should always mention the heterogeneity measures so that the readers don’t find it false.

Conclusion

This editorial makes you understand what meta-analysis is, along with the basic step-by-step process to conduct a meta-analysis. The methods here are a general structure that includes framing a research question, searching the literature, choosing the right meta-analytical method, and at last, finding out the result and reporting it.

Creating a Video Abstract for your Research

Want to create an impactful abstract that persuades the readers to read your article?  Here’s an interesting solution – Video Abstracts

Introduction

What is a video abstract?

A video abstract is an innovative way to explain your work to the public and researchers outside of your field that adds value proposition. This 3-5 minute video lets you conclude all the accomplishments in your research work in a journal article.

Importance of Video Abstract

Video Abstract uses a method to create a video summary by using a series of fixed pictures or moving images that let the readers get a brief idea about the targeted topic within a short period of time rather than scrolling through a theoretical and lengthy abstract.

Techniques for Observation Video Abstraction

  1. Color-based Techniques: It is used because of its indifference and stability against changes in direction and size.

 

  1. Event-Based Video Abstraction: It combines motion analysis with video skimming to create an event-based method that examines the optical flow to find exciting events and compare them to previous data. Events of interest are usually kept in video abstracts.

 

  1. Motion-Based Technique: It addresses pixel-to-pixel frame differences and optical flow.

 

  1. PowerPoint Presentation: This is the most common and popular technique that delivers insightful images and clean slides which is used for video abstract.

 

  1. Animations: With the help of accessible animation software tools, dynamic or stationary picture graphics can be created which is a cost-effective method.

 

  1. Combination types: This technique can create meaningful abstracts by gathering high activity material and being threshold-independent, but it is a domain-specific approach.

 

Video abstraction suggested for observation

  1. Pre-selection
  2. Attribute abstraction
  3. Colour and appearance
  4. Technical Specifications

 

Guidelines for Video Submission

  1. Incorporation of video picture files as supplementary electronic materials should be done by the author.
  2. After the approval of the manuscript, the author is asked to upload the video pictures to MOMO (Make Our Movies Open) (via website).
  3. This is done by an associate editor who is in charge of video submissions and e-mail management.
  4. At this point, the steps to upload the video are provided.
  5. Once the video is published in the Online First Article, no modifications can be henceforth. Therefore, the writers are advised to upload a new file to MOMO and get a different ID code in case they want to opt for any modifications.
  6. In case of query, kindly contact the head editor.

 

Conclusion

A number of video apps count on video abstraction, such as categorization, reading, and recapture. The various techniques used for a better video abstraction is a key point to keep in mind. Also, the technicalities and specifications mentioned must be employed for an innovative and interesting video abstract for a journal article.

Post Acceptance Changes of Manuscripts

Proofs are supplied to the corresponding author once your manuscript has been approved for publication. Once approved by the corresponding author, your paper is assembled into an issue of the journal and published in its final form. After providing your proof revisions, you are not expected to provide additional input as the piece’s author.

There are three stages between submission and publication in a peer-reviewed journal:

  • The time elapsed between submission and the first decision.
  • The amount of time required for the authors to revise
  • The time it takes from acceptance to publishing. 

    Peer review occurs when an article is submitted to a target journal. However, multiple processes are frequently only known to the related author. When you make a manuscript submission to a journal, it travels quite a distance, and the manuscript status is tracked with the help of the manuscript number. If a paper is accepted after peer review, it goes through proof development and a review procedure before being published. This process is a time-consuming process that necessitates a thorough examination of your manuscript’s publication-ready version. If you make a mistake here, it may be tough to fix!

     Changes to Authorship

    Requests for adding an author before publication are less difficult to arrange than requests after publication. Requests to add authors before publication typically comes from inside the existing author team. When requests are made after publication, they rarely come from inside the existing team but rather from a disgruntled team member who believes they deserved authorship but were not properly credited.

     Changes to Manuscript

    Copyediting the manuscript carefully ensures that it is accurate, clear, legible, written in good English, and adheres to the journal’s house style. Typesetting in the journal’s format for print or pdf, with the appropriate fonts and symbols, and with the figures in their final sizes, is what typesetting entails.

    After consulting with co-authors, the corresponding author returns the PDF to Proof checking Services. Authors can assist by asking just necessary modifications (such as typos). Authors may believe their figures are too small and request that they be expanded. After the corresponding author and Proofreading Services have agreed on all revisions, a subeditor rereads the entire proof and cycles with the typesetter until it is finally correct.

    Errors Spotted by Readers

    Aside from what has been said above, inaccuracies in published articles may be discovered by readers other than the author. In such circumstances, the editor must seek clarification from the appropriate author. Furthermore, if necessary, agree on the phrasing of a corrigendum or erratum that meets the author’s and reader’s approval.

    The most serious cases involving requests for revisions to published articles occur when a reader reports that an article is:

    • Replicated or plagiarised
    • Data that has been faked or manipulated
    • There are catastrophic errors that the writers cannot repair or explain in an erratum or corrigendum. 

      Conclusion

      Requests to make changes to manuscripts after approval are quite rare. Editors do not keep a systematic record of such incidents. As a result, it isn’t easy to estimate how frequently this occurs or what the most common causes are.

Co-author Guide and Acceptance letter in a Journal

Some journals may send Co-Authors an email containing deep links to confirm Co-Authorship. Corresponding Authors may also be allowed to control the Other Author verification procedure by the Journal.

Who is the Co-author?

A Co-author is someone who has made a significant contribution to a journal publication. They also share accountability and responsibility for the outcomes.

If an article has more than one author, you’ll choose the corresponding author. This person will be in charge of all article correspondence and sign the publishing agreement on behalf of all authors. The corresponding author is in charge of ensuring that all of the authors’ contact information is correct.

Roles of Co-author

  • The corresponding (submitting) author is exclusively responsible for communicating with Scientific Reports and handling co-author correspondence. Do Correction and proofreading of manuscripts. Handle modifications and re-submissions of updated manuscripts until the manuscripts are accepted.
  • Accepting and signing the Author Publishing Agreement on behalf of all necessary co-authors and obtaining the signature of any third-party rights owners.
  • Arranging for APC (article processing charge) payment. Under Open Access Agreements, the corresponding author’s affiliation is considered to assess eligibility for discounted or waived APCs.
  • Act on behalf of all co-authors in responding to post-publication requests from all sources, including issues about publishing ethics, content reuse, and the availability of data, materials, and resources.

There are several compelling reasons why you should work together on a publication. Collaborations in research are one of the finest reasons. Collaborations in research might be one of the most satisfying aspects of your scientific career. Working with “masters” in your profession or experts from other fields can substantially extend your horizons and provide you with access to knowledge, methods, infrastructure, and labor. Collaborations in research frequently result in two or more publications. It is common for one publication to be driven by your partners in these instances. Your contribution is recognized with a co-authorship, several co-authorships, or, in ideal cases, an asterisk indicating “equal contribution.”

Acceptance letter for co-authors

Journal editors exclusively send emails to the corresponding author, not the co-authors. The corresponding author is the journal’s sole point of contact. The corresponding author’s responsibility is to relay the editor’s messages to the co-authors. Journal editor cannot send individual acceptance letters to every co-author. As a result, You should contact the associated author and request that the acceptance letter is forwarded to you if you require it.

Conclusion

Based on the Authors position in the research process and paper preparation, authors can be designated as the lead author, first author, co-author, or corresponding author. The corresponding author is in charge of the manuscript during the submission, peer review, and production processes.

From submission to publication, all communication will be with the relevant author. However, there is a recurrent dispute over whether or not an article can have more than one associated author. Some or several co-authorships may enhance scientific cooperation and reciprocal intellectual stimulation and expand your publication list and fill gaps in your publication history.  It is better to avoid publishing too many papers with many co-authorships.

Publishing your research and improving the visibility

Choosing the right journal and publication of your research findings

Publications are the top metric the world will use to measure your success as a researcher. Publishing the research papers in high-impact and peer-reviewed scholarly journals is the ultimate target for most of the researchers.

One of the commonest mistakes that researchers do is the submission of their research paper to a random or unsuitable journal and hence forcing the editors to reject the paper in the technical check stage. Therefore, selecting a suitable journal makes the difference between acceptance and rejection.

There are certain suggestions which can be considered when selecting a right journal for your research article:

  1. Examine the nature of the journal before submitting your valuable paper to them. Check if they are legit or predatory.
  2. The scope of the journal must be considered before submitting the paper to the target journal.
  3. The quality of any journal is assessed on the basis of how many abstracting and indexing services cover that journal.
  4. Impact factor of a journal is used as an indicator of the significance of a journal in its category (field).
  5. Rapid but authentic publication can shorten the peer-review process.

Know more about 

Increasing the visibility of your research paper

Each year, millions of research articles are getting accepted for publication in the journals and that number is significantly improving. Hence, it is becoming necessary to formulate different methods to make the research articles significant among others. Improving the visibility and audience reach of your article should not be restricted to only the post-publication of the manuscript; rather, it should begin from the time the research paper is drafted.

Pre-publication activities

  • Writing a convincing and effective article
  • Writing a brief and yet comprehensive abstract with use of keywords for indexing purposes
  • Selecting a list of potential keywords (the keywords used must be popular among researchers in your field)
  • Making your research article accessible to all scholarly readers through Open Access publication service which is now provided by almost all reputed publishers, moreover, if the option is not available, you can still post your pre- or post-publication prints to a repository or server such as SHERPA/RoMEO database, Brock Digital Repository, etc
  • Participating in conferences and meetings and discuss about your under review research or the research synopsis
  • Sharing the synopsis of the research (on sites such as ResearchGate)
  • Self engagement in ongoing discussion or starting a new about the relevant ongoing research projects with colleagues or researchers from different labs or universities

Post-publication activities

  • Talking about your recent publication with researchers even if they are not directly related to your field, this includes emailing the copies of your published research paper to researchers.
  • Creating a personal website or blog dedicated for your research and sharing regular updates on it
  • Using platforms such as ResearchGate account to circulate your research paper among specific group of researchers and following their updates as well
  • Finding few social media applications which match you and your purposes, some of the widespread social media platforms are Facebook, Twitter and LinkedIn. Create an audience of scholars and researchers and share all of your research papers and upcoming projects. Keep the connections engaged with blogs and research synopses.

Statistical Hypothesis Testing- Steps, Errors, Interpretation

What is hypothesis testing?

Hypothesis testing is used to determine whether a premise is valid or not in relation to a statistical parameter. The goal of hypothesis testing is to make decisions about a population based on the interpretation of hypothesis testing on sample data drawn from the population data.

How Hypothesis Testing is done?

The testing of a hypothesis is done by forming a null and alternate hypothesis, where the null hypothesis states that the prevailing belief or premise in relation to a statistical parameter is true whereas the alternate hypothesis states that the prevailing belief or premise in relation to a statistical parameter is not true and thus alternate hypothesis is accepted.

Null and alternate hypothesis are mutually exclusive in nature. If one is true automatically another hypothesis becomes false and thus both are proposed simultaneously in relation to a statistical parameter.

Let us go through the steps of conducting hypothesis testing-

  1. Propose a null hypothesis (H0) and alternate hypothesis (Ha) is proposed in relation to the statistical parameter you want to interpret from the population.
  2. Specify the significance level (α) for accepting or rejecting the null hypothesis where the significance level is about the probability of error when the null hypothesis is true. The researcher decides on the significance level based on research problem. Generally, as a thumb rule, an alpha level of 0.05 (5%) is used.
  3. Conduct the experiments, and collect data to run statistical tests.
  4. Select an appropriate statistical test to calculate test statistics and p-value (In the null hypothesis, the p-value measures the probability of obtaining the observed results).
  5. Analyze the output and form conclusions.

Interpretation of the test results

Based on the output of the statistical test, the p-value is compared with the significance level (α). If the p-value is lower than the threshold level of acceptable error specified in the alpha value then observations are considered to be significant. Usually, the significance level for a study is set at 0.05 or 5%. A p-value that is below the significance level indicates that your results were statistically significant and supported the alternative hypothesis. If your p-value was greater than the significance level, then the results were statistically insignificant.

The interpretation of statistical hypothesis testing thus helps in making decisions on the validity of the hypothesis on the population data based on the statistical tests drawn on sample data drawn from that population data.

Types of Error in Hypothesis Testing

There are few types of errors that occur during hypothesis testing based on discrepancy between actual results and statistical results. Those types of errors are-

  1. Type I error – Type I errors are false positive errors when results appear to be statistically significant but they are actually purely by chance or the result of unrelated factors. This type of error can be prevented by choosing a higher alpha value (α).
  2. Type II error – Type II errors mean failing to reject the null hypothesis when it is actually false. This is not the same as accepting the null hypothesis as a test can only conclude whether to reject the null hypothesis. A type II error occurs when the statistical study failed to conclude the effect of stimuli on a statistical parameter when there actually was. This type of error can be prevented by increasing the statistical power of the study. The Type II error rate is also known as beta (β).

Hypothesis Testing

Hypothesis testing is the process of testing validity of a hypothesis or a supposition in relation to a statistical parameter. Hypothesis testing is used by analysts to determine whether or not a hypothesis is reasonable. For example, hypothesis testing could be used to find whether a certain drug is effective or not in treating headache. It uses data from a sample to draw conclusions about a statistical parameter. Hypothesis testing is an important step as it validates statistical parameter which could be used in making conclusions or inference about population or large sample data.

Types of Hypothesis

In data sampling, different types of hypothesis is used to examine whether a sample is positive for test hypothesis or not.

  1. Alternative Hypothesis (H1) – This hypothesis states that there is a relationship between two variables (where one variable affects the value of other variable). The relationship that exists between the variables is not due to chance or coincidence.
  2. Null Hypothesis (H0) – This hypothesis states that there is no relationship between two variables. It states that the effect of one variable on another is entirely due to chance, with no empirical explanation.
  3. Non-Directional Hypothesis – It states that there is a relationship between two variables, but that the direction of influence is unknown.
  4. Directional Hypothesis – It states the direction of effect of the relationship between two variables.

Alternative hypothesis and null hypothesis is used to study data samples to find a possible pattern to form a statistical hypothesis that can be validated through hypothetical testing. Alternative hypothesis and Null hypothesis cannot be true at the same time as they are mutually exclusive. Similarly, Non-directional and directional hypothesis cannot be true at the same time as they are mutually exclusive.

Methods of Hypothesis Testing

  1. Frequentist Hypothesis Testing- This is the traditional approach to hypothesis testing. It involves making assumptions on current data and comparing prior knowledge about hypothesis with posterior knowledge of the hypothesis to form a conclusion on the hypothesis. One of the subtypes of this approach is Null Hypothesis Significance Testing.
  2. Bayesian Hypothesis Testing- It is one of the modern methods of hypothesis testing. In this method prior probability of hypothesis from past data and current data is used to find posterior probability of the hypothesis.

The Bayes factor, which is a key component of this approach, represents the likelihood ratio between the null and alternative hypotheses. This factor indicates the plausibility of either of the two hypotheses formed for hypothesis testing.

 

Techniques of Hypothesis Testing

There are few commonly used Tests: Z-Test, T-Test, Chi squared Test and F-Test.

  1. Z Test- A z test is performed on a population with independent data points that follows a normal distribution and has a sample size of larger than or equal to 30. When the population variance is known, it is used to determine whether the means of two populations are equal. Z test statistic is compared to the crucial value and the null hypothesis of z test is rejected if the z test statistic is statistically significant.

 

 

 

Where,

Z= Z-test

X̄ =sample average

µ=mean

s=standard deviation

  1. T Test – A t-test is an inferential statistic that is used to see if there is a significant difference in the means of two groups that are related in some way. This test is also called as Student test. It is used when variables are continuous, sample size is less than 30, and population standard deviation is not known. T statistic is used to arrive at a conclusion on whether to accept the hypothesis or reject the hypothesis.

 

 

 

Where,

t= Student’s t-test

m= mean of sample

µ= assumed mean

s= standard deviation

n= number of observations

  1. Chi squared Test – A chi-square statistic is a test that evaluates how well a model matches actual data. For using Chi squared test the data used must be random, mutually exclusive, taken from independent variables from a large sample.

 

 

where:

c=Degrees of freedom

O=Observed value(s)

E=Expected value(s)

There are two types of χ2 test – the test of independence, and goodness-of-fit test. A χ2 test for independence can show us how likely it is that random chance can explain any observed difference between the actual frequencies in the data and these theoretical expectations.

  1. F Test – Any statistical test with an F-distribution under the null hypothesis is known as an F-test. It is generally used to compare statistical models that have been fitted to a data set to find which model best fits the population from which the data were sampled. To perform an F-test, the population must have an f distribution and the samples must be random. If the f test findings are statistically significant, the null hypothesis is rejected otherwise, it is not. F statistic for large samples:

 

 

Where,

σ12  = variance of the first population

σ22  = variance of the second population

Reporting Guidelines for Medical Research

Health researchers might use a reporting guideline as a straightforward, structured tool when preparing publications.

What is a Reporting Guideline?

A reporting guideline is a collection of facts that you include in a manuscript to ensure that it can be, for example:

  • When a reader understands what you’re saying,
  • A researcher confirmed the findings.
  • A doctor will use it to make a medical decision, and
  • For conducting a systematic review.

Reporting guideline is used to prepare high-quality research reports since it requires the article to meet the checklist’s requirements. You can explain to the peer reviewer the checklist used to assess the document. Following this protocol, researchers can publish their findings with or without minor revisions.

What are the different types of Reporting Guidelines?

The EQUATOR Network (Enhancing the Quality and Transparency of Health Research) is a global effort to improve the quality of research publications. It includes a complete set of reporting guidelines and other resources to aid in the improvement of reporting.

A list of all of the reporting guidelines for many different study designs is available to assist you in reporting your research.

  • PRISMA – Preferred Reporting Items for Systematic Reviews and Meta-analyses – for reporting the systematic review
  • CONSORT – Consolidated Standards of Reporting Trials – for reporting randomized controlled trials
  • STROBE – Strengthening the Reporting of Observational Studies in Epidemiology – its flow diagram for reporting observational study
  • MOOSE – Meta-analysis Of Observational Studies in Epidemiology – for reporting observational epidemiological meta-analysis
  • STARD – Standards for the Reporting of Diagnostic accuracy studies – for reporting diagnostic and prognostic accuracy of the study
  • SPIRIT – Standard Protocol Items: Recommendations for Interventional Trials – for clarifying the report
  • REMARK – Reporting Recommendations for Tumor Marker Prognostic Studies – for Oncology and Genetic studies
  • COREQ – Consolidated criteria for reporting qualitative research – for enhancing the quality of the report
  • CARE – Consensus-based clinical case reporting – for precise reporting
  • TRIPOD – Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis – for Prognostic studies
  • RIGHT – A Reporting Tool for Practice Guidelines in Health Care – for Clinical practice guidelines
  • SRQR – Standards for reporting qualitative research – for Qualitative research
  • ARRIVE – Animal Research: Reporting of In Vivo Experiments – for Animal preclinical studies
  • SQUIRE – Standards for QUality Improvement Reporting Excellence – for Quality improvement studies

 

Advantages of Reporting guidelines 

  • The quality of reporting will improve if you follow the reporting guidelines.
  • Only publications that strictly follow the guidelines will be published in a high-impact journal.
  • Assists the reviewer in ensuring that all pertinent information has been reported.

 

Conclusion

Your article must provide a clear and comprehensive overview of your findings. Complete reporting makes it easier for editors, peer reviewers, and readers to comprehend what you did and how you did it.

Poorly reported research can skew the literature, resulting in findings that can’t be repeated or utilized in future meta-analyses or systematic reviews. Editors and peer reviewers will be able to analyze your article better if you follow these standards since they will understand what you did.

Reasons for Facing Desk Rejection

There are numerous causes for rejection; however, desk rejection or rejection without peer review is one of the most annoying emails an author gets. It’s not uncommon to have a paper rejected. To decide how to continue from there, you must first understand why the journal editor did not send it out for peer review.

It’s critical to comprehend the reasons behind a rejection before deciding on a strategy. It’s usually simple to extract the criticism about your work from a peer review report and organize your next steps accordingly. It can be more difficult to comprehend why your work was rejected by the journal editor without having been sent out for review. This blog post summarizes the five most prevalent reasons for rejection without peer review to assist you decides on a resubmission strategy.

  1. If the manuscript does not meet the journal’s objectives or scope

It’s doubtful that the paper will be approved if it won’t be of interest or value to the journal’s readers. When deciding which magazine to submit to, always read the Aims and Scope to get a sense of the types of papers the journal is searching for. In other words, does your work, beyond its scientific scope, fit the journal’s unique geographical region? Distinct journals have different scopes, which are usually quite narrow. Make sure your manuscript is appropriate for the journal you want to submit it to.

  1. If the results of your research were not significant or new enough

Journal editors frequently reject papers without submitting them for peer review because they do not believe the manuscript is appropriate for their publication. If you submit your manuscript to a publication with a diverse audience in terms of expertise, the editor may decide that your study isn’t of sufficient interest to a large enough section of the readership.

It’s also possible that the journal editor isn’t sure that your findings are substantial enough to warrant publication. This implies they may not anticipate their having far-reaching repercussions for your field of study. It is usually also necessary for journals with high journal impact factors if the research is original and has not been published before, even if only in part.

  1. If plagiarism is too high

Plagiarism should be avoided at all costs. You could be accused of plagiarism if you intentionally or unintentionally plagiarized the work of other researchers. Manuscripts are run through various plagiarism detection software programmes by publications. If there is more than 20% duplication in a manuscript, it will be returned to the authors for editing. The publishers may report the material as plagiarized if that percentage is significantly greater. If you effectively plagiarize your own work by merely repackaging it, you may be called out.

  1. If your data is inadequately presented, and you applied inappropriate methods

Editors of broad-read journals typically cover a significant percentage of a research field, thus they are unlikely to be specialists in your research topic. As a result, people are likely to skip over your Results section and instead focus on your data when evaluating the quality of your research.

Even if the journal editor is unfamiliar with your research topic, you may expect them to have a strong awareness of what is going on in your field in general. As a result, if they see that you employed an obsolete method or didn’t use a strategy properly, your work will most likely be rejected right away.

  1. If there are issues with language, writing, and spelling

The document’s language, organization, and any tables or figures must all be of sufficient quality to be examined; if this is not possible, the paper will be rejected. Your abstract, cover letter, references, and, if applicable, your discussion and/or conclusions section are usually of particular interest to journal editors (s). It’s usually a good idea to have someone else look through your paper before you submit it; the second set of eyes can help you catch any mistakes you may have overlooked.

There are other causes for submission rejection, but these are only a few of the most typical issues cited by journals. For busy researchers, it may appear to be a lot of work, and this is where we, ManuscriptEdit may help.

How to fix 5 Desk Rejection

Rejection from a journal is no one’s cup of tea but then it’s a reality that a large number of the article gets rejected across different journals.  Also, Journals mention the acceptance rate or the changes of the article getting rejected on their web page.

High impact or top journals routinely reject the majority of the articles. Few changes can improve the chances of successful publication.

  • Non-accordance with the journal’s aim & scope

Very often while selecting a journal we feel that the aim and scope match our field of work; however, it’s not the case.  We need to read the former a couple of times along with the recently published articles to be doubly sure regarding the scope of journals.

  • Lack of proper language and presentation style

Language is an important medium for sharing scientific know-how. Grammatical and scientifically correct language and abiding by the journal formatting guild lines are mandated for avoiding desktop rejection.

  • Plagiarism and simultaneous submission to more than one journal

Copying someone’s work as our own data is a violation of professional ethics. Always give due acknowledgment to someone else’s data while writing. Never submit your work to multiple journals at a time. The author should wait till the editorial process of one journal is over or they have got a clear cut no from the journal.

  • Ambiguity in methodology

The process of the study or the research protocol is mentioned in the methodology. It should be clear and systematic. Any flaw in the methodology section represents non-clarity on how the study was conducted.

  • Abide by journal’s formatting guidelines

Stick to the journal’s requirement for word count, font, line spacing, and margin. Also, be careful with the number of figures and tables allowed and their format for submission. The placement of the figure and table is also crucial that is, whether it should be at the end of the manuscript or within the text itself. Reference formatting both in text and in the list at the end of the manuscript needs lots of precession.