Sharing nursing dissertation data with an analysis service requires more than removing names from a spreadsheet. Before sending files, check whether external assistance and the proposed data transfer are permitted, identify the minimum information needed and agree how it will be handled.
This is a checklist for an actual handover. If you need to describe the whole research lifecycle in your methods chapter, use our data management section guide. For choosing an analysis task, read how to request data-analysis help.
Check two different permissions first
The first question is academic: does your university permit the proposed methods consultation or analysis assistance, and must it be acknowledged? The second concerns research information: may these particular files be shared with this recipient for this purpose?
Permission to receive academic help does not automatically authorise sharing participant data. Likewise, access to a dataset does not automatically allow you to send it to an external service.
Check the approved protocol, participant information, consent arrangements, data-use agreements and institutional guidance relevant to your project. If the position is unclear, ask your supervisor or the responsible research or data-governance contact before transferring files.
Start with a description of the problem
You may be able to obtain an initial scope assessment without sending raw records. Provide the research question, study design, objectives, variable definitions and the analysis already planned.
For example, explain that the project compares a questionnaire score between two groups and provide the scoring documentation. The reviewer can identify further information needed before any data transfer is considered.
Do not send a full clinical export merely to ask which test might fit. Agree whether the task requires actual data, existing output or only methodological context.
Identify direct and indirect identifiers
Direct identifiers may include names, contact details, patient numbers or staff identifiers. Indirect identification can arise through combinations of dates, locations, job roles, rare events or small groups.
For interviews, examine the text as well as the filename. A participant may identify another person or describe a distinctive event. For spreadsheets, inspect free-text fields, hidden sheets, comments and embedded links.
Do not make unsupported assurances that a dataset is anonymous because one column was removed. Record what has been removed, what remains and who is authorised to assess the disclosure risk.
Understand pseudonymisation accurately
ICO guidance distinguishes pseudonymisation from anonymisation. Pseudonymised information remains personal data, and replacing identifiers with codes does not by itself make a dataset anonymous (ICO, n.d.a; n.d.b).
Keep any re-identification key under the approved arrangements and do not send it simply because the working dataset uses participant codes. The analyst’s task should not require discovering who the participants are.
Assess the remaining material in context. Information that appears harmless alone may become identifying when combined with another field or external knowledge. Use your institution’s assessment process rather than relying on a generic checklist as proof of anonymity.
Agree the minimum files needed
| Task | Potential starting material | Check before sending |
|---|---|---|
| Methods consultation | Question, design and codebook | Whether examples reveal any participant information |
| Output interpretation | Output, syntax and variable definitions | Whether output contains identifiers or small-cell details |
| Running analysis | Authorised working dataset and documentation | Sharing permission, necessary fields and transfer route |
| Qualitative review | Approved anonymised extracts and coding notes | Consent, contextual identification and third-party mentions |
This table describes possible material, not universal requirements. The approved scope and permissions determine which files can be shared.
Clarify who will access the information
Ask the service to identify who will work on the files and whether any additional software, subcontractor or platform will receive them. A promise of confidentiality does not explain the processing arrangements by itself.
Questions to raise include where the files will be stored, which tools will process them, who can access them and whether any transfer outside the approved environment is proposed. Refer any uncertain arrangement to the institution responsible for the data.
The ICO’s data-sharing resources address governance and accountability as well as technical measures (ICO, n.d.c). Do not assume that a secure transfer channel resolves every permission or processing issue.
Confirm a permitted transfer method
Use the route approved for your project and institution. Agree it before uploading information. Avoid public links or a shared folder with access wider than the task requires.
Check the recipient and folder permissions, confirm exactly which files are included and record the transfer date. If encryption or password protection is part of the approved process, follow the institution’s instructions.
Do not improvise an alternative channel because a file is large or the deadline is close. Ask for an approved way to complete the handover.
Discuss retention, return and deletion
Ask how long working copies, output and backups will be retained and how deletion will be handled. Do not invent a retention period: the approved plan, agreements and institutional requirements control it.
Specify what you need returned. This may include syntax, a documented analysis trail, labelled output and a list of unresolved queries. Keep the authorised master research files under your own approved arrangements.
Also agree how problems will be reported. If a file is sent to the wrong recipient or unexpected identifying information is discovered, follow the institution’s incident procedure promptly. Do not conceal it or continue sharing while the position remains unresolved.
Example: planning a survey analysis handover
An MSc student wants support interpreting a confidence-score analysis. The initial request includes the design, objectives, questionnaire scoring rules and codebook. The student checks permission for outside assistance and whether sharing the output is allowed.
Before sending anything, the student examines the output for case labels and small-group information. If the task requires a dataset, the authorised transfer and handling arrangements are agreed separately.
The example shows a sequence: define the task, establish permission, minimise the material and confirm handling. It does not authorise any particular transfer for your own project.
If sharing is not permitted
Ask whether a consultation using non-identifying variable descriptions can resolve the issue. An authorised university support service may offer another route. You may also be able to discuss your own interpretation without transferring participant-level records.
A simulated demonstration can explain a software method, but it must remain clearly labelled as simulated. Do not replace real observations with fabricated values or report illustrative output as dissertation findings.
Before-send checklist
- The university permits the requested assistance.
- The research information can be shared with this recipient for this purpose.
- The task and minimum files are defined.
- Direct and contextual identifiers have been assessed.
- Pseudonymised data are not incorrectly described as anonymous.
- Access, tools, storage and any additional recipients are understood.
- The transfer route is authorised.
- Retention, deletion and incident procedures are clear.
- The original records and decision trail remain protected.
Frequently asked questions
Can I send data after deleting names?
Not automatically. Permissions and the remaining identification risk still need checking.
Can I send only output?
Sometimes, depending on the task. Output may still contain sensitive details, so assess it before sharing.
Does anonymisation make external assistance acceptable?
No. Your university’s academic-assistance rules are a separate requirement.
Can the analysis service grant sharing permission?
The service cannot replace the authority of the institution, data owner or approved research arrangements.
Discuss the task before sending research files
Use nursing data analysis and SPSS support to describe the question and analysis problem first. For taught Master’s projects, see MSc nursing dissertation support.
Send a description of the task and permissions position. Agree the appropriate materials before any transfer.
Conclusion
Before sharing nursing dissertation data, define the task, confirm authority to share and minimise the material. Check identifiers and handling arrangements separately from academic-assistance permissions. Keep the approved master files and an accurate record of decisions.
References
- Information Commissioner’s Office (n.d.a) Pseudonymisation. Available at: ICO pseudonymisation guidance (Accessed: 12 October 2026).
- Information Commissioner’s Office (n.d.b) Introduction to anonymisation. Available at: ICO anonymisation guidance (Accessed: 12 October 2026).
- Information Commissioner’s Office (n.d.c) Data sharing. Available at: ICO data-sharing resources (Accessed: 12 October 2026).
