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If available data cannot support the original scope, do not force them to answer a broader question than they can address. Determine what evidence the question actually requires, assess whether other data can provide it, and narrow or reformulate the question transparently when necessary.
Read Guide →Research scope creep occurs when new questions, variables, populations, methods, analyses, or other demands gradually enter a project without sufficient reconsideration of its original purpose and capacity. Prevent it by making the baseline scope explicit and requiring every proposed addition to justify both its intellectual value and its methodological cost.
Read Guide →One study begins to look like several when its questions require substantially independent populations, evidence, methods, analyses, or conceptual rationales and no longer need to be answered together. Related questions can belong to the same research program without being forced into a single study.
Read Guide →Your research question should establish what the study needs to investigate, but feasibility determines what you can responsibly promise to answer. The strongest scope is usually developed by refining the question and practical constraints together.
Read Guide →A delimitation protects a study when it creates a defensible boundary while preserving the question that matters. It becomes problematic when difficult but essential parts of the question are excluded mainly to make the research easier.
Read Guide →A population delimitation becomes a substantive generalizability question when extending findings beyond the studied population matters and there are plausible reasons the findings may differ in the target population. The issue is not simply who was excluded, but whether that exclusion changes the inference you want to make.
Read Guide →A study period needs scientific justification when time affects what can be observed, compared, or inferred. The relevant question is not simply how long data collection takes, but whether the chosen period matches the phenomenon and research question.
Read Guide →Should your study be quantitative, qualitative, or mixed methods? Learn how to choose a research approach based on the question you need to answer rather than the method you already know.
Read Guide →Knowing a research method well is a genuine advantage, but familiarity should not be the main reason you choose it. The method must first be capable of producing the evidence needed to answer your research question.
Read Guide →Starting with a preferred method is not automatically wrong, but the final study should not exist merely to give that method something to do. A defensible research question must matter independently and require evidence the chosen method can appropriately provide.
Read Guide →The ideal method for a research question may be beyond your current resources, expertise, access, or institutional capacity. The solution is not automatically to abandon the question or substitute whatever method is convenient, but to determine what can change without changing what the study actually claims to answer.
Read Guide →Research questions often need refinement once practical constraints become clear. The problem begins when adaptation no longer makes the original question feasible but instead replaces it with a different, less meaningful question simply because it fits the method you can use.
Read Guide →Qualitative analysis can be labor-intensive, but that is not sufficient reason to replace a qualitative question with a quantitative one. Time should influence the feasibility and scope of a study without determining what kind of evidence the research question requires.
Read Guide →A replication asks whether prior evidence or a previous claim holds up under another test. An extension moves beyond that prior work to investigate something additional, although a single study can deliberately do both.
Read Guide →Using a different population does not automatically make your research a new study. The key question is whether you are testing the same scientific claim in a new population or whether the population change creates a meaningfully different research question.
Read Guide →A replication does not need a completely new research question to make a contribution. A strong justification explains which existing claim remains uncertain, why resolving that uncertainty matters, and how the new study provides evidence the literature does not yet have.
Read Guide →A methodologically weak study can deserve replication, especially when its claim matters and remains influential. The challenge is deciding whether repeating the original design would test the finding or merely reproduce the weakness that made the evidence uncertain.
Read Guide →Original data can be extremely useful when planning and interpreting a replication, but replication normally generates new data rather than reanalyzing the original dataset. The more important question is whether the published methods and available materials provide enough information to conduct an interpretable new test.
Read Guide →A failed replication does not necessarily end the scientific question. Another replication can be valuable when it can distinguish among plausible explanations for the disagreement rather than merely adding a third result to an unresolved dispute.
Read Guide →A literature full of studies does not necessarily need another dataset. When existing evidence has never been synthesized properly, the first research gap may be a synthesis gap rather than a data gap.
Read Guide →Another primary study is not always the best way to reduce uncertainty. When sufficiently comparable studies already exist, meta-analysis may provide a more precise and informative answer, but only if pooling them is methodologically defensible.
Read Guide →Heterogeneity does not automatically mean that more primary research is needed. Another study is most useful when it can test a plausible source of variation that existing evidence cannot resolve.
Read Guide →Studies do not have to be identical to be synthesized, but they must be comparable in ways that matter to the research question. When differences undermine a meaningful common inference, statistical pooling may be inappropriate even though systematic review remains possible.
Read Guide →International evidence does not automatically remove the need for local research. A new study is most defensible when local conditions create meaningful uncertainty about whether existing findings apply, how they apply, or what decision should follow.
Read Guide →A local context does not need to be dramatically different before another study is justified. What matters is whether a specific difference could plausibly change the finding, mechanism, implementation, interpretation, or decision.
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