Research assumptions in a nursing dissertation explain the premises your study relies on. A useful section identifies what is being accepted, why that position is reasonable and how uncertainty affects the research. It should make the study more transparent without presenting expectations as proven facts.
Students sometimes fill this section with statements that all participants are honest, all measures are valid and the sample represents every nurse. Those claims are too strong unless supported by the actual design and evidence. This guide shows how to write more careful statements using original nursing examples.
Follow your university’s required structure. Some programmes request a separate assumptions section; others expect the relevant reasoning within methodology, measurement or researcher-positioning discussions. Do not add an unrequested chapter simply because an online example includes one.
What is a research assumption?
A research assumption is a premise underlying the study’s design, knowledge claims or interpretation. It may concern what can be learned from participants, how a concept can be measured or whether records contain information suitable for the question. The premise should matter to the research, rather than state something obvious.
Saint Peter’s University’s dissertation guide distinguishes assumptions from hypotheses: assumptions support the design, whereas hypotheses are propositions examined through research (Saint Peter’s University, n.d.). The guide is an institutional example, so apply its principle within your own nursing programme’s requirements.
An assumption also differs from a result. A survey might rely on respondents understanding a question about missed care. That does not establish how much care was missed. Similarly, interviews may be appropriate for exploring experiences without making every account a complete record of clinical events.
Use a simple test: if this premise were seriously wrong, would the study’s design or interpretation change? If the answer is yes, it may deserve explicit discussion. If the statement is merely convenient or unrelated to the research question, it probably adds little.
Distinguish assumptions from other dissertation elements
| Element | Purpose | Fictional nursing example |
|---|---|---|
| Research assumption | Identify a premise supporting the enquiry | Nurses can provide meaningful accounts of their handover experiences. |
| Hypothesis | State a proposition to examine | Handover interruptions are associated with lower perceived clarity. |
| Delimitation | Explain a chosen boundary | The study includes adult inpatient nursing staff only. |
| Limitation | Describe a constraint and its consequence | Self-reported accounts may be affected by recall. |
| Statistical assumption | State a condition relevant to a particular model or test | Observations are independent under the proposed analysis. |
These elements can be connected without being interchangeable. Choosing a single site is a delimitation; restricted applicability beyond that site may be a limitation. Assuming staff understand a survey item is a premise; piloting the item is a method for examining that concern.
Keep hypothesis writing in its own section. Our nursing dissertation hypothesis guide explains that separate task. For chosen boundaries, use our scope and delimitations guide.
Which types of assumptions may need discussion?
Not every study needs the same list. Identify premises from the research question, the chosen design and the materials you will actually use. Avoid importing assumptions from a quantitative dissertation into a qualitative project simply because the wording sounds academic.
Philosophical assumptions concern what you regard as knowable and how knowledge can be developed. Capella University’s research guidance distinguishes questions about reality, knowledge, values and methods (Capella University, n.d.). You can explain these ideas in plain language, but the position should fit the research rather than operate as a decorative label.
Practical assumptions concern the data-generating process. For example, a questionnaire may require participants to recognise the time period being asked about. Interview research may depend on participants being able to describe relevant experiences. Secondary analysis may rely on documentation meaning the same thing across records.
Measurement assumptions concern the relationship between a recorded value and the concept being studied. A burnout scale score is not automatically an adequate measure for every population. Evidence for the instrument and its use in your setting belongs in the methodology, alongside relevant checks.
Analytical assumptions concern the specific approach used to interpret data. Some can be examined directly. Others depend on study design or substantive judgement. Do not present all analytical conditions as matters that can safely be taken for granted.
A practical method for writing the section
Begin by tracing the study from question to conclusion. Write down the proposed data source, how information will be collected or selected, how it will be analysed and what claims the findings could support. At each stage, ask what must be reasonably credible for that step to work.
Next, separate premises from issues you can investigate. Questionnaire comprehension can be explored through appropriate piloting. Missing entries in records can be audited. Statistical conditions can sometimes be assessed with diagnostics. Calling an issue an assumption does not remove the need for an available check.
For each remaining premise, write four linked parts:
- Premise: what the study relies on.
- Reason: why it is relevant and plausible.
- Safeguard or check: what was actually done, or is proposed.
- Consequence: how uncertainty affects interpretation.
You do not need a lengthy paragraph for every item. However, a bare list leaves the reader unable to judge the reasoning. Connect the premise with your study and avoid generic assurances that the research is valid.
Use our Chapter 3 methodology checklist to place the reasoning within the wider chapter.
Quantitative nursing example: questionnaire responses
Weak wording: “All nurses will answer the questionnaire honestly, so the findings will be accurate.”
This statement guarantees behaviour the researcher cannot guarantee. It also jumps from an assumption to a conclusion about the whole dataset. Honesty alone does not eliminate misunderstanding, recall difficulty or non-response.
More careful wording for a proposed study: “The survey relies on participants understanding the questions and providing accounts they consider accurate. Clear instructions and a planned pilot will help identify comprehension problems. However, responses may still be influenced by recall and social desirability, which will be considered when interpreting the findings.”
Change the language for a completed study. State that a pilot was conducted only if it actually happened. Explain its purpose and findings in the methods, rather than inventing a safeguard to make the assumptions sound stronger.
Likewise, do not assume a convenient sample represents all nurses. If the study cannot support population-wide estimates, define the population reached and describe the appropriate limits on interpretation.
Qualitative nursing example: participant accounts
Weak wording: “Participants’ experiences are objective facts and the researcher has no influence on the findings.”
This wording may conflict with an interpretive design. Interviews involve questions, relationships and interpretation. An account can provide meaningful insight while reflecting the participant’s perspective and the interview context.
More careful wording: “The enquiry treats participants’ accounts as meaningful perspectives on their clinical experiences. These accounts are interpreted within the interview context rather than treated as complete factual records. The researcher will examine how their nursing background and questioning influence interpretation.”
This example is appropriate only if it matches the chosen methodological position. It does not prescribe one philosophy for every qualitative study. For further analysis guidance, read our thematic analysis guide.
Explain reflexive procedures where they belong. An assumptions section should introduce the premise without copying the whole positionality discussion or analysis method.
Secondary-data and literature-review examples
A secondary-data project may rely on the meaning and consistency of existing records. For example, a discharge timestamp might represent departure from the ward in one dataset but administrative completion in another. Before relying on the field, investigate its documented meaning.
A careful statement could explain that the analysis uses timestamps as defined in the authorised data dictionary, alongside any available checks. If definitions differ or documentation is incomplete, discuss the consequence. Do not claim that clinical records are automatically accurate because they originated in a healthcare organisation.
A literature review may rely on sufficient reporting in included studies to extract relevant information. However, peer review alone does not establish that every study is methodologically strong. Search, screening and critical appraisal are part of evaluating the evidence.
A suitable premise might be that published reports can provide information relevant to the review question, while recognising incomplete reporting and publication bias. Report what can be extracted and appraised; do not fill gaps with invented participant details or findings.
For a broader design discussion, see our secondary research dissertation guide.
Research assumptions are not a substitute for statistical checks
Keep general study premises separate from conditions required by a statistical procedure. Independence, model specification and distributional conditions require consideration appropriate to the design and analysis. They cannot all be established through a single normality test.
For example, repeated measurements from the same participant are related. Declaring them independent in an assumptions paragraph does not change the data structure. The analysis must account for that structure using an appropriate method.
Similarly, a statistically significant result does not confirm that every study premise was true. Check the actual test requirements, the data and the design. Our statistical-test selection guide and SPSS normality guide address those more specific questions.
This article focuses on writing and justifying research premises. It does not replace model diagnostics, instrument evaluation or a complete statistical analysis plan.
Where should assumptions appear?
Use the location required by your handbook. Saint Peter’s University’s guide places assumptions among Chapter 1 elements, whereas other templates may integrate relevant discussion into methodology. Neither arrangement should be copied without checking the local brief.
When assumptions appear in Chapter 1, keep them concise and direct the reader to methodological justification. When they appear in Chapter 3, relate them to design, sampling, measurement or interpretation as appropriate. Avoid reproducing identical paragraphs in both chapters.
Revisit the section after data collection or evidence review. A proposal describes planned safeguards. A completed dissertation must report what actually occurred. If a premise became doubtful, identify that change and consider its effect on the discussion.
The section should remain consistent with the Chapter 1 study framing and the final conclusions.
Research assumptions in a nursing dissertation: an audit table
Before drafting paragraphs, build a private table with four columns: premise, basis, possible check and remaining uncertainty. This exercise helps distinguish a justified position from a sentence included merely because an example dissertation used it.
For a survey, the premise might concern comprehension of a defined term. The basis could include published measurement work and an appropriate participant information sheet. A possible check could be a pilot, if permitted and relevant. Remaining uncertainty might concern different interpretations that the available check cannot fully resolve.
For interviews, the premise might concern the usefulness of accounts for understanding experiences. The basis should fit the philosophical and methodological position. A useful check may involve reviewing the interview approach, while remaining uncertainty concerns the influence of context and the researcher’s interpretation.
Do not describe the table as proof that the study is sound. It is a reasoning tool. Its purpose is to show where evidence, methodological action or qualified interpretation is needed. Only the relevant conclusions need to appear in the dissertation.
Reviewing research assumptions in a nursing dissertation after data collection
The completed dissertation should not preserve proposal wording automatically. Look again at each premise after recruitment, data collection and analysis. Ask whether the experience of conducting the study gives you reason to strengthen, qualify or reconsider it.
Suppose a questionnaire pilot revealed that participants interpreted a question differently. If the question was revised before collection, report the revision accurately. If inconsistent interpretation remained possible, acknowledge the uncertainty rather than claiming the assumption was verified for every respondent.
Alternatively, a record-based project might discover changes in coding practice over time. That finding affects whether values can be compared as originally intended. Discuss the issue with your supervisor and revise the procedure or claims as appropriate. An assumptions section cannot repair a mismatch by ignoring it.
Maintain an honest account of timing. A planned safeguard is different from a completed action, and a later check is different from one built into the original design. Clear reporting allows readers to understand how the research developed.
How to respond to feedback about unsupported assumptions
If a supervisor writes “justify this assumption”, identify the exact premise being challenged. Do not answer by adding general citations at the end of the paragraph. Ask what each source actually supports and whether it applies to your population, instrument or research context.
Then decide whether the problem is weak explanation, missing evidence or an unsuitable premise. Weak explanation may need a clearer connection with the design. Missing evidence may require further reading or a feasible check. An unsuitable premise may require reconsidering the method rather than better wording.
For example, a source showing that a measure performed well in one population does not automatically establish its suitability elsewhere. Explain the similarity and relevant differences, then describe what your study can realistically assess. Where uncertainty remains, avoid converting it into a guarantee.
Keep a brief revision record linking the comment, the action and the affected section. Check that the revised assumptions agree with the limitations and discussion. Otherwise, one chapter may acknowledge uncertainty while another continues to claim that the premise was unquestionably true.
The aim is a defensible account of reasoning. You do not need to eliminate every uncertainty before research can be useful. You do need to identify important premises, investigate what can be checked and limit conclusions where the evidence warrants caution.
Frequently asked questions
How many research assumptions should I include?
Use the relevant premises required to explain your study, following the brief. There is no universal number. Avoid adding weak assumptions to reach an arbitrary total.
Can I assume an instrument is valid?
Explain the evidence supporting its intended use and any relevant checks. Do not use an assumptions paragraph to replace measurement-quality assessment.
Are assumptions the same as hypotheses?
No. A hypothesis is a proposition the study examines. An assumption is a premise underlying how the enquiry proceeds or how information is interpreted.
What if an assumption is not supported?
Review the design, analysis or interpretation with your supervisor. A doubtful premise may require a different procedure, a qualified conclusion or explicit discussion of a limitation.
Conclusion and final checklist
Read each assumption and ask whether it is necessary, justified and consistent with your method. Check which concerns can be investigated, describe only genuine safeguards and explain remaining uncertainty. Remove any sentence that assumes the answer to your research question.
If you need feedback on assumptions or chapter alignment, send your brief, research question and current draft. Methodology support can help clarify the reasoning while preserving your approved design and research responsibilities.
For personalised feedback on your research assumptions, explore our focused nursing dissertation section review and request a quote for the sections you need checked.
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References
Capella University (n.d.) Research philosophy and assumptions – SOE. Available at: Capella University study guide (Accessed: 5 October 2026).
Saint Peter’s University (n.d.) Writing Chapter One: Problem and Procedures. Available at: Crafting the Dissertation (Accessed: 5 October 2026).
