Nursing Dissertation Chapter 4 should make the findings transparent, traceable and easy to connect with the research questions. A strong results chapter shows who or what was analysed, reports the evidence produced by the approved method, presents tables or themes clearly and preserves uncertainty.
It should not hide unexpected findings, invent explanations or turn the results section into a second discussion chapter. The exact boundary between findings and discussion varies by programme, but the evidence trail should always remain clear.
What Chapter 4 needs to do
- Organise findings around the approved questions, hypotheses or synthesis plan.
- Report participant or study flow, denominators, missing data and exclusions transparently.
- Use tables and figures when they improve understanding rather than duplicate prose.
- Report estimates, uncertainty and effect sizes where relevant—not p-values alone.
- Present qualitative themes with de-identified evidence and visible analytic reasoning.
- For reviews, report study flow, characteristics, appraisal and synthesis according to the review method.
Start with the research questions
Place each research question or objective beside the finding that answers it. If a table, statistical test or theme does not connect with an approved objective, decide whether it belongs in the main chapter, an exploratory section or an appendix.
This prevents Chapter 4 from becoming a catalogue of outputs generated merely because software or coding produced them.
Report participant or study flow
Readers should be able to reconstruct how the final analytic sample or evidence set was reached.
For primary research, report the relevant stages such as eligibility, recruitment, exclusions, attrition and final analysis. Explain important differences in denominators caused by missing data.
For systematic reviews, PRISMA 2020 recommends transparent reporting of records identified, screened, excluded and included, with reasons for full-text exclusion where appropriate (Page et al., 2021). Numbers in the flow diagram, methodology and narrative must agree.
Describe the analysed sample or evidence set
For quantitative studies, include the characteristics required to understand the findings, such as age, clinical variables, group sizes, baseline measures and missingness where relevant.
For evidence reviews, report features such as study design, setting, sample, intervention or phenomenon, follow-up and other characteristics that influence interpretation.
Avoid presenting every collected variable. Include information that describes the sample, helps assess comparability or supports interpretation.
Report quantitative results accurately
Quantitative results should normally identify what was tested, relevant descriptive statistics, the statistical estimate, uncertainty and the immediate finding. SAMPL guidance recommends providing enough numerical information for readers to understand and evaluate the analysis rather than reducing results to “significant” or “not significant” (Lang & Altman, 2015).
Where relevant, report:
- valid group sizes and denominators;
- means and standard deviations or medians and interquartile ranges;
- test statistics and degrees of freedom;
- exact p-values;
- effect sizes or association estimates;
- confidence intervals; and
- the amount and handling of missing data.
A p-value is not a measure of clinical importance or the probability that a hypothesis is true. Interpret it alongside study design, effect magnitude and uncertainty (Wasserstein & Lazar, 2016).
For SPSS-specific results, use the nursing SPSS results-chapter guide and SPSS output interpretation guide.
Build tables that can stand on their own
Every table should have an informative title, clear row and column labels, consistent units and notes defining abbreviations or statistical symbols. State denominators when they are not obvious and keep decimal places consistent.
The narrative should identify the important pattern rather than repeat every cell. If a table already shows the group means, confidence interval and p-value, the text should explain the central result instead of reproducing every number.
Use figures selectively
Figures are useful when they reveal distributions, trends, group differences or participant flow more clearly than prose. Label axes and units, use honest scales and remove decorative effects that exaggerate differences.
Every figure should answer a question. Do not include a chart simply because SPSS, Excel or another program generated it.
Present qualitative themes as findings
Qualitative findings should present themes, categories or other analytic products rather than a list of quotations. Define each theme, explain its boundaries and show how it answers the research question.
COREQ supports transparent reporting of interview and focus-group studies, including the relationship between the data and reported themes (Tong et al., 2007).
Use concise, de-identified extracts to demonstrate the interpretation. Include variation and deviant cases where they affect the analysis rather than implying that every participant expressed the same view.
A quotation supports an interpretation; it does not replace one.
Report evidence-synthesis findings according to the review method
For a review dissertation, Chapter 4 may include study flow, characteristics, appraisal findings and the output of the planned synthesis.
Systematic, scoping and integrative reviews do not produce identical results sections. The reporting structure should follow the approved review method and research question rather than a generic template.
Keep extracted findings distinct from the dissertation author’s interpretation. The discussion can then evaluate patterns, contradictions, limitations and nursing implications.
Report non-significant and unexpected results
Do not hide a result because it does not support the hypothesis. Report approved analyses consistently, including non-significant, contradictory and unexpected findings.
A non-significant result does not automatically prove that no effect exists. Limited power, imprecise measurement or wide confidence intervals may matter. Likewise, label unplanned or post-hoc analyses clearly rather than presenting them as though they were specified from the beginning.
Keep results and discussion distinct
A useful distinction is:
- Results: What was observed or produced by the approved analysis?
- Discussion: Why might it have occurred, how does it compare with previous evidence, how confident are we and what does it mean?
Some qualitative or integrated formats allow more interpretation within the findings chapter, but the reader should still be able to distinguish evidence from broader discussion.
Use the discussion chapter structure guide once the findings are stable.
Protect confidentiality in results reporting
Remove direct identifiers and assess deductive disclosure, particularly with small samples, rare roles or unusual conditions. Aggregate small cells where the approved governance process requires it.
Edit quotations only to protect identity or improve readability without changing meaning, and indicate meaningful editing where appropriate.
The NMC Code requires nurses to respect privacy and confidentiality and to handle information appropriately (Nursing and Midwifery Council [NMC], 2018). University ethics approval and the data-management plan may impose additional requirements.
Run a results-integrity audit
Compare Chapter 4 with the methodology, analysis plan and source output. Check that:
- sample sizes and denominators agree across text, tables and figures;
- the reported tests match the methodology;
- planned primary analyses are reported or their omission is explained;
- qualitative themes can be traced to coded evidence;
- review-study counts agree with the flow diagram;
- units and decimal places are consistent;
- unexpected findings have not been selectively removed; and
- new interpretation has not been disguised as a result.
Results by study type
| Finding type | Chapter 4 responsibility | Avoid |
|---|---|---|
| Quantitative | Accurate estimates, uncertainty, tests, units and denominators | Treating significance as clinical importance |
| Qualitative | Transparent themes supported by de-identified evidence | Quotation lists without analysis |
| Review | Study flow, characteristics, appraisal and synthesis output | Mixing extracted evidence with unsupported opinion |
| Unexpected | Honest reporting with exploratory labels where needed | Selective omission or post-hoc certainty |
Common Chapter 4 mistakes
- Reporting tests that were not justified in the methodology.
- Presenting percentages without denominators.
- Copying raw software output directly into the main chapter.
- Interpreting p-values as clinical importance.
- Using quotations without explaining the theme.
- Hiding non-significant or contradictory findings.
- Adding a new analysis because the planned result was disappointing without labelling it exploratory.
- Changing participant or study counts between tables, figures and narrative.
Frequently asked questions
Should Chapter 4 include interpretation?
Programme conventions differ. Many dissertations separate results from discussion, while qualitative and integrated formats may include limited analytic interpretation. Follow the approved structure and keep broader comparison with literature for the discussion unless instructed otherwise.
How many tables should a results chapter contain?
There is no fixed number. Use tables only when they improve understanding and avoid duplicating the same information in prose.
Do I report non-significant findings?
Yes. Report approved analyses transparently and interpret uncertainty carefully rather than hiding findings that do not support expectations.
How many quotations should support a qualitative theme?
There is no universal number. Use enough varied, de-identified evidence to demonstrate the analytic claim without turning the chapter into a transcript catalogue.
What if my Chapter 4 sample differs from Chapter 3?
Explain recruitment, exclusions, attrition, missing data and deviations transparently so the analysed sample can be reconstructed.
Academic integrity
Developmental support may explain reporting, review alignment or check output against the approved method. It should not invent participants, data, approvals, quotations, references, results or clinical events.
Related Nursing Guides
- How to Fix a Weak Nursing Dissertation Discussion Chapter
- Nursing Dissertation Chapter 1: Frame the Study
- Nursing Dissertation Chapter 2 Structure: Literature Review Checklist
Conclusion
A strong Chapter 4 makes the evidence trail visible. Organise findings around the research questions, report the analysed sample transparently, present quantitative, qualitative or review findings according to the design and preserve uncertainty rather than forcing a preferred result.
For an existing results chapter that needs methodological and structural review, use the nursing dissertation editing service. For project-specific statistical work, use the nursing data-analysis service.
References
- Lang, T. A., & Altman, D. G. (2015). Basic statistical reporting for articles published in biomedical journals: The SAMPL Guidelines. International Journal of Nursing Studies, 52(1), 5–9. https://doi.org/10.1016/j.ijnurstu.2014.09.006
- Nursing and Midwifery Council. (2018). The Code: Professional standards of practice and behaviour for nurses, midwives and nursing associates. https://www.nmc.org.uk/standards/code/
- Page, M. J., McKenzie, J. E., Bossuyt, P. M., et al. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
- Tong, A., Sainsbury, P., & Craig, J. (2007). Consolidated criteria for reporting qualitative research (COREQ): A 32-item checklist for interviews and focus groups. International Journal for Quality in Health Care, 19(6), 349–357. https://doi.org/10.1093/intqhc/mzm042
- Wasserstein, R. L., & Lazar, N. A. (2016). The ASA statement on p-values: Context, process, and purpose. The American Statistician, 70(2), 129–133. https://doi.org/10.1080/00031305.2016.1154108
