Facebook as a tool for communication, collaboration, and informal knowledge exchange among members of a multisite family health team
Bibliographic record
Abstract
OBJECTIVE: To implement and evaluate a private Facebook group for members of a large Ontario multisite Family Health Team (FHT) to facilitate improved communication and collaboration. DESIGN: Program implementation and subsequent survey of team members. SETTING: A large multisite FHT in Toronto, Ontario. PARTICIPANTS: Health professionals of the FHT. MAIN OUTCOME MEASURES: Usage patterns and self-reported perceptions of the Facebook group by team members. RESULTS: At the time of the evaluation survey, the Facebook group had 43 members (37.4% of all FHT members). Activity in the group was never high, and posts by team members who were not among the researchers were infrequent throughout the study period. The content of posts fell into two broad categories: 1) information that might be useful to various team members and 2) questions posed by team members that others might be able to answer. Of the 26 team members (22.6%) who completed the evaluation survey, many reported that they never logged into the Facebook page (16 respondents), and never used it to communicate with team members outside of their own site of practice (19 respondents). Only six respondents reported no concerns with using Facebook as a professional communication tool; the most frequent concerns were regarding personal and patient privacy. CONCLUSION: The use of social media by health care practitioners is becoming ubiquitous. However, the issues of privacy concerns and determining how to use social media without adding to provider workload must be addressed to make it a useful tool in health care.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".