SU‐F‐E‐11: Perception and Implementation of Collaborative Documentation Technologies Among Medical Physics Educators and Industry Professionals: A Current Practice Survey
Bibliographic record
Abstract
Purpose: Collaboration on documents and manuscripts plays a central role in conveying medical physics concepts between interdisciplinary teams, necessary for knowledge‐building, acquiring funding, and translating scientific concepts to applied medical solutions. Conventional tools and emerging internet‐based solutions are used in generating and disseminating physics documents among teams. This research aimed to gain insights on how medical physics professionals and educators are using collaborative documentation software and team practices. Methods: An online survey based on a modified version of the Noel & Roberts (2004) collaborative documentation survey in 'Computer Supported Cooperative Work’ was used to collect data from 102 industry practitioners and educators engaged primarily in medical physics. Items includes 30 scaled and qualitative assessments of software use, inputs, time spent on documentation tasks and related activities (meetings, leadership, task assignment, etc.), number of collaborators, documentation volume and practices, revision and publication strategies, and attitudes toward documentation software. Results: Of 102 respondents, 74 completed all survey sections, and 58/74 (78%) reported using collaborative document technologies, but only 35% of these were fully satisfied with the technology. A total of 27/58 (47.37%) reported collaborative documentation tools assisted in meeting established deadlines. Most collaborative documentation projects spanned weeks, and required a commitment of 17.68 hours/week (2 – 80, median 15). Between 2–100 synchronous meetings lasting 1–5 hr/meeting were required, most commonly held before starting writing (43.64%) to discuss technical contents (85.96%), document requirements (61.40%), assign tasks (54.39%), or resolve team conflicts (52.63%). Results were presented as a visual infographic, potentially useful as a teaching aid. Conclusion: While reportedly easy to use, most online collaborative tools did not fully meet physicist documentation needs, including deficiencies in security, load times, information presentation capabilities, and role assignment. These insights can help improve collaborative documentation software development and training programs for new authors in medical physics fields. The author is an employee of GE Healthcare. This study was completed through the author's academic doctoral work and no funding or other interests were provided by the author's employer.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".