PP339 Topic: AS09–Global Health/Resource Limited Setting/Health Inequalities/Impact of Global Warming/Other: IMPACT OF IN-PERSON VS VIRTUAL ATTENDANCE ON THE QUALITY OF INTERACTIONS IN CONSENSUS CONFERENCES: COMPARISON OF PALICC AND PALICC-2
Bibliographic record
Abstract
Aims & Objectives: Limited research has explored the comparative impact of consensus conferences conducted in different formats (in-person versus virtual attendance). This study aims to assess and compare the perceived quality of interactions between PALICC (Pediatric Acute Lung Injury Consensus Conference, 2012-2015, conducted in person) and PALICC-2 (2020-2022, predominantly virtual). We also assess the impact on carbon footprint, reported in a separate abstract. Methods: A validated self-administered questionnaire was utilized to assess participants’ perceptions across nine qualitative aspects of their involvement in consensus development, for both formats. Results: We received 49 answers (84% participation). The participants expressed higher satisfaction with in-person events across most components of interactions. They reported feeling more engaged in discussions, finding it easier to express their opinions, noticing greater openness among experts to alternative viewpoints, and experiencing better interactions, socialization, collaboration, and networking at in-person conferences. However, participants felt that virtual events were more effective in enhancing global representativeness, diversity and inclusion, reducing environmental impact, saving time, and for work/life balance. The majority favored a future consensus conference model that alternates between virtual and in-person meetings (n=24) or adopts a completely hybrid model (n=20). Conclusions: While experts from PALICC and PALICC-2 found the in-person model to facilitate better engagement, discussions, and consensus formation, the virtual modality was perceived to offer significant benefits such as global representativeness, inclusion, and environmental impact reduction. Future consensus conferences should incorporate a substantial virtual participation component, while further exploration is needed to determine the optimal balance and modality of in-person participation. Keywords: interactions, consensus conference
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.206 | 0.029 |
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".