| Course | HS880 Doctoral Project III: Data Collection and Analysis |
|---|---|
| Unit | Unit 3 |
| Paper type | Data management protocol |
| Length | About 870 words, 6 pages double-spaced |
| Format | APA 7 student paper |
| School | Purdue University Global |
| Program | Doctor of Health Science (DHSc) |
| Updated | October 2026 |
Free sample paper for HS880 Unit 3
Nothing in the Survey File Can Reach a Name: A Unit 3 Data Management Protocol for a Survey and Interview Study
[Student Name]
Purdue University Global
HS880: Doctoral Project III: Data Collection and Analysis
Unit 3 Data Management Protocol
[Instructor Name]
[Date]
The network, systems and timelines are composite; the methods sources cited are real.
Principles
Three principles govern every decision. First, survey responses are anonymous: no one, including the student, can link a response to a person. Second, interview data are confidential: the research team knows who was interviewed, but identities are protected and removed before analysis. Third, every file has a defined end: a date after which it is destroyed or archived without identifiers.
Data Item One: Survey Responses
Collected by the university's survey platform. Fields: shielding frequency, domain items, site type in three categories, years in practice in four bands and training program type. No name, email, employee number or exact site is collected. Site type replaces site because several outpatient sites employ four or fewer radiographers, and a response from such a site, combined with years in practice, could identify a person. Stored on the platform and downloaded to the university's secure research drive. Access: the student and the statistical consultant. Retained for seven years under university policy, then destroyed.
Data Item Two: Interview Contact Form
Collected through a separate form on the same platform, reached by a link on the survey's final page. Fields: name, email, site type and a preferred contact time. Because the form is separate, its entries cannot be matched to survey responses. Access: the research coordinator only. Destroyed once interviews are scheduled or declined, no later than [60] days after the survey closes.
The contact form and the survey share a platform but not a file, so even a person who wanted to connect a volunteer to their answers could not.
Data Item Three: Interview Recordings
Recorded on a university-issued encrypted recorder or within the university's video platform, never on a personal phone. Transferred to the secure drive within 24 hours and deleted from the device. Access: the student and the transcription service under a signed confidentiality agreement. Destroyed after each transcript is verified against its recording, no later than [90] days after the interview.
Data Item Four: Transcripts
Produced by the transcription service and checked by the student. Before analysis, the student removes names, sites, colleagues' names, patients' details and any distinctive event that could identify a person, replacing them with bracketed descriptions. Each transcript carries a participant code. A key linking codes to names is kept in a separate password-protected file accessible only to the student and destroyed at the end of analysis. Deidentified transcripts are shared with the second coder, whose role in checking coding consistency is part of the study's rigor plan (O'Connor & Joffe, 2020). Retained for seven years.
Data Item Five: Codebook and Analysis Files
The codebook is kept in numbered versions, each with a date and a log of changes. Coding is done in qualitative analysis software on the secure drive. Coding memos are dated and filed with the version they concern. These files form the audit trail that lets another researcher follow how transcripts became findings, which directed content analysis depends on for credibility (Hsieh & Shannon, 2005). Retained for seven years.
Access List
Student: survey data, recordings, transcripts, codebook, key. Research coordinator: contact form only. Second coder: deidentified transcripts and codebook. Statistical consultant: survey data only. Committee: deidentified results and codebook on request. No one at Wrenfield Health has access to any study data.
Reporting Rules
Results by site type will be suppressed where a cell contains fewer than [five] respondents. Quotations will be checked for identifying details before use, and no quotation will be attributed to a site type if that site type had fewer than [three] interviewees. Integration tables will report domains and themes, not individuals (Fetters et al., 2013).
Backups and Devices
The secure research drive is backed up nightly by the university, so no separate backup copies will be made. Study files will not be stored on laptops, email or cloud services outside the university's approved platforms. When the student works away from campus, files are opened through the university's virtual desktop, which keeps them on the secure drive. Printed transcripts will not be used; if a printout is needed for a coding meeting, it will be shredded the same day.
Training
Before handling any data, the research coordinator, second coder and transcription service will complete the university's human subjects training and read this protocol. The student will walk the coordinator through the separation between the survey and the contact form, since that separation depends on the coordinator never asking volunteers about their survey answers. Anyone joining the team later will receive the same briefing and sign the same confidentiality agreement.
Breach Response
If any identifying data are exposed, the student will notify the review board within [five] working days, as the approved protocol requires, and will record the event in the deviation log.
Review
The protocol will be reviewed by the student's chair before collection begins and again after the first [five] interviews, to confirm that deidentification is working as intended.
References
Fetters, M. D., Curry, L. A., & Creswell, J. W. (2013). Achieving integration in mixed methods designs: Principles and practices. Health Services Research, 48(6 Pt 2), 2134-2156. https://doi.org/10.1111/1475-6773.12117
Hsieh, H.-F., & Shannon, S. E. (2005). Three approaches to qualitative content analysis. Qualitative Health Research, 15(9), 1277-1288. https://doi.org/10.1177/1049732305276687
O'Connor, C., & Joffe, H. (2020). Intercoder reliability in qualitative research: Debates and practical guidelines. International Journal of Qualitative Methods, 19, 1-13. https://doi.org/10.1177/1609406919899220
The Purdue Global HS880 Unit 3 instructions
Unit 3 usually asks candidates to write a data management protocol covering every type of data the study collects. Three to six pages is common. For each data item, instructors expect the source, fields collected, storage location, who may access it, how it is protected and when it will be destroyed or archived. Candidates should distinguish anonymous from confidential data and explain how identifiers are removed. Many prompts ask for reporting rules that protect participants in small groups and for an audit trail for qualitative analysis. Plans should say who receives training, how devices and backups are handled and what happens if data are exposed. The protocol should match the approved application.
How this HS880 Unit 3 example is built
The protocol states three principles: anonymity for survey data, confidentiality for interview data and a defined end for every file. Five data items follow, each with source, fields, storage, access and retention; the survey item explains why site type replaces site. The highlighted sentence explains why the contact form and survey cannot be linked. Transcript handling covers deidentification, participant codes and a separate key. The codebook item describes versioning as an audit trail. An access list, rules for suppressing small cells and quotations, backup and device rules, training for every team member, a breach procedure and a review after five interviews close the protocol.
Reading the HS880 Unit 3 grading rubric
Data management protocols are commonly evaluated on completeness across data types, protection of participants, clarity of access and retention, alignment with regulations and the approved protocol, and practicality. Protection of participants usually weighs most; graders look for a credible separation between identities and responses. Completeness rewards protocols that include contact forms, recordings and analysis files, not only the main dataset. Access and retention earn points when every role and date is named. Small-cell rules and quotation checks show awareness of indirect identification. Practical detail about devices, backups and training makes a protocol believable. Clear organization by data item completes the score. Reviewers frequently test a protocol by asking who could see a given file on a given day, so precise answers matter.
Common HS880 Unit 3 mistakes, and how to avoid them
A common weakness is calling data anonymous when it is only confidential, for example when a contact form sits in the same file as survey answers. Another is overlooking indirect identifiers, such as exact site combined with years in practice at a small location. Some candidates forget recordings on personal phones or transcription services. Others set no destruction dates. Protocols that describe security in general terms without naming who has access are hard to approve. If your study collects other data, perhaps health records or focus group recordings, send a list of what you will collect, and a protocol can be prepared that assigns each file a place, an access list and an end date.
Get an HS880 Unit 3 example written to your instructions
Data management requirements differ across universities and sites, and so do the templates. Tell us the data types you will collect and the storage your institution provides, and attach the Unit 3 prompt with the rubric. The sample places every file, separates identity from answers and flags the retention rules your policy must fill. First custom sample free, 24-48h. The paper above is an original model document written by our desk, not a submitted student paper and not an official Purdue University Global document.
More HS880 papers and DHSc samples
- HS880 Unit 1: Survey and Interview Recruitment Plan
- HS880 Unit 2: Low Survey Response Discussion Post
- HS880 Unit 4: Codebook Draft
- HS880 Unit 5: Coding Memo
- HS880 Unit 6: Seminar Reflection
- HS880 Unit 7: Descriptive Results Summary
- HS880 Unit 8: Analysis Output Narrative
- HS880 Unit 9: Deviation and Limitation Memo
- HS880 Unit 10: Results Chapter Draft
- HS865 Unit 3: Shielding Literature Synthesis Matrix
- HS810 Unit 3: Stakeholder Power Map
- HS860 Unit 3: Proposal Assumption Discussion Post
- HS820 Unit 3: Dutch and Swiss Comparative Matrix
HS880 Unit 3 questions, answered
What is the difference between anonymous and confidential data?
Anonymous data cannot be linked to a person by anyone, including the researcher. Confidential data can be linked, usually through a key, but the researcher protects that link. A survey with no identifiers and a separate opt-in form can be anonymous; interviews are normally confidential, since the researcher knows who spoke. Invitations and consent should use whichever term is accurate.
Why is a small site a confidentiality risk?
Because details that seem harmless can identify someone when few people share them. If a site has four radiographers and a quotation is attributed to a senior radiographer there, colleagues may recognize the speaker. Replacing site names with types, merging small groups in tables and removing distinctive details from quotations all reduce that risk.
What belongs in an audit trail for qualitative data?
Records that let someone follow how raw data became findings: transcripts, dated codebook versions, memos explaining coding decisions, notes from consensus meetings and a log of changes to categories. Lincoln and Guba linked such records to dependability and confirmability. Keeping them as you go is far easier than reconstructing them when the results chapter is due.
Where can I find a free HS880 Unit 3 sample paper?
The full Unit 3 data management protocol is posted here, covering surveys, contact forms, recordings, transcripts and codebooks for a radiographer study.
Why replace site with site type in the survey?
Several sites have four or fewer radiographers, so an exact site combined with years in practice could identify someone. Site type keeps responses anonymous.