The personal use of Facebook by public health professionals in Canada: Implications for public health practice
Bibliographic record
Abstract
Objective: We explored attitudes, beliefs, and experiences of Canadian public health professionals (PHPs) and their personal use of Facebook to assess views of online professionalism and blurring between their professional and personal lives.Methods: Ten public health organizations assisted in distributing an online questionnaire to their members. The questionnaire explored Facebook use, personality factors, and beliefs about online etiquette.Results: Among 621 respondents, 77% had a personal Facebook profile. Participants were unlikely to disclose personal information on Facebook. Generally, participants felt posting workday information online was inappropriate; however, 15 and 26% thought it acceptable to vent about the general public, and post comments about people or beliefs that oppose accepted public health views, respectively. Approximately one in four participants (26%) believed that the personal use of Facebook has an impact on one's role as a public health practitioner. One in eight participants (12%) was likely to search for members of the public with whom they had previous professional contact. The need for popularity and awareness of consequences were key predictors of participants' disclosure on Facebook.Conclusions: Overlap between the private and public lives of Canadian PHPs exists on Facebook, and highlights the potential for damage to public health credibility. Future research should evaluate any real-world impact of comments and venting (via personal Facebook profiles) on public health credibility, especially as public health continues to embrace social media for health interventions where online contact between individual employees of public health organizations and members of the general public is increased.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".