Clarifying a working definition for ‘precision communication’: a scoping review of medical literature on communication
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
AIMS: While "tailored communication" and "precision medicine" have been well-defined in medical literature, the concept of "precision communication" in healthcare has yet to be clarified. We sought to review how "precision communication" has been used in the medical literature to date and propose a working definition for this term. MATERIALS & METHODS: We searched seven medical literature databases from inception until 22 May 2024, for articles using terms related to "precision communication." Multiple reviewers screened titles/abstracts and full-texts; an initial pool of full-text articles underwent thematic analysis to clarify relevant themes for inclusion. Data regarding the use of the term "precision communication" were manually charted and analyzed descriptively. RESULTS: Of the 7,648 articles identified, 21 full-text articles were included in the final descriptive analysis. These articles highlighted the personalization of tailored communication to patient characteristics, its impact on clinical outcomes, and the recipients of "precision communication." The latter may distinguish "precision communication" from similar terms: where "tailored communication" was mostly applied to undefined groups, we propose that "precision communication" is precise toward specific patient subpopulations, paralleling the use of genomics in precision medicine. CONCLUSIONS: From this review, we defined precision communication as "the personalization of communication to subpopulations."
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it