Data Collection, Evidence Synthesis, and Documentation

Data Collection, Evidence Synthesis, and Documentation

You have an approved project plan. Now the real work begins: gathering data with discipline, analyzing it honestly, and writing a report that a clinical supervisor or credentialing reviewer could pick up and trust. This lesson walks you through each phase so your capstone becomes a true demonstration of professional practice.

Executing Your Data Collection Plan

Follow your approved methodology exactly unless a documented reason forces a change. Every session begins with a Project Data Log entry that records the date, the method you used, the raw result, and any deviation from the plan. If you skip a step or substitute a measurement, note it immediately—omitting deviations is a form of research misconduct, even in a student project.

If your project involves phantom positioning exercises, work with the same phantom and the same exposure settings each session so your data is comparable. Score each image against your standardized evaluation rubric before moving to the next exposure; do not revisit scores after you have seen later results, because that introduces bias. If your project is a reject-analysis audit of de-identified images, use only the department reject-analysis form and never record any information that could identify a patient—this is both an ethical requirement and a HIPAA obligation. If your project is a quality-control (QC) log review, pull records from the Course 6 equipment logs and transfer values into your spreadsheet exactly as written; do not round or adjust raw numbers at the collection stage.

Patient and radiation safety reminder: No project activity justifies exposing a live patient beyond their prescribed clinical procedure. Phantom work and image audits are the safe alternatives for student capstone projects. If you observe a safety concern while auditing clinical images or reviewing QC logs, report it immediately to your clinical supervisor and document it in your log.

The Midpoint Progress Report

At the halfway point of your data-collection phase, you submit a Progress Report of at least two pages. This document serves two purposes: it forces you to interpret your data before it is complete, which sharpens your thinking, and it gives your instructor a chance to redirect you before problems compound.

The progress report should summarize what data you have collected so far, identify any unexpected findings (an image batch with far more positioning errors than anticipated, or QC values that trend in an unexpected direction), describe any methodology adjustments you made and why, and offer a preliminary interpretation of what the data may mean. Be honest. If your data collection is behind schedule, say so and explain your recovery plan. Your instructor will return written feedback within five business days. Students who are significantly off track will meet individually with their faculty advisor.

Analyzing Your Complete Dataset

Once all data are in the log, apply the analysis method that fits your data type.

Quantitative data (exposure index values, repeat rates expressed as percentages, measurement readings): calculate the mean, the range, and frequency counts for each category. A simple table in your spreadsheet can produce these automatically. Use a bar chart or line graph to display trends across time or across image groups.

Qualitative data (written observations about positioning technique, notation of error types): group similar observations into themes, count how often each theme appears, and present those counts in a table. This converts narrative notes into comparable categories.

Keep your analysis at the descriptive level. You are not expected to perform inferential statistics (such as t-tests or chi-square tests) unless your instructor has specifically approved that approach. Accurate description is more valuable than inappropriate statistical testing.

Writing the Full Draft Report

Your draft must contain every required section. Think of it as the professional report you would write if your department director asked you to investigate a clinical quality problem.

• Abstract (150–250 words): State the problem, what you did, what you found, and what it means. Write this last.
• Introduction: Explain why the topic matters clinically. Cite at least two peer-reviewed sources that provide background or document the problem in the literature.
• Methods: Describe what you did in enough detail that another student could replicate it. Include your data log structure, your rubric or audit form, and your analysis approach.
• Results: Present your data objectively. Include at least one table and one figure. Do not interpret here—just report what the numbers show.
• Discussion: Connect your results to clinical practice. Reference ARRT content areas related to your findings (for example, image production and evaluation, or radiation protection). Acknowledge limitations of your project.
• Conclusion: One to two paragraphs summarizing the main takeaway and any practice recommendation.
• References: At least eight sources formatted in APA or AMA style consistently throughout. Bushong and Carlton/Adler are acceptable references; peer-reviewed journal articles strengthen your literature base.

Submit the complete draft through the LMS portal before the deadline. Your instructor will use an analytic rubric to score the draft and return markup. A score of at least 35 out of 50 is required to move to the finalization phase. If you score below that threshold, you will meet with your instructor and resubmit within two weeks.

Professional and Ethical Standards

Everything you collect, record, and report must be accurate and honest. Fabricating or altering data, even for a student project, violates the ARRT Standards of Ethics. Your future credentials depend on your ethical record. Treat your capstone data with the same integrity you will bring to clinical imaging.