Soon after the previous issue of the International Journal on Dental Hygiene, the world has changed
Bibliographic record
Abstract
Although circumstances and the degree to which Members of our Federation have been affected by the COVID-19 virus differ a great deal from country to country, many Dental Hygienists around the world were unable to work. To support and inform her members, IFDH gathered more than 50 resources and guidelines on its website. See www.ifdh.org. The IFDH fielded a survey supported by Proctor & Gamble (Crest/Oral-B) to better understand the impact of the COVID-19 pandemic on the dental hygiene profession and identify opportunities to support global dental hygienists, dental therapists and oral health therapists through these difficult times. The survey was sent to 34 national associations to field to their members between 5 May and 31 May 2020. 9866 respondents completed the survey, representing 30 countries. The countries with the largest representation included the United States (83%), Canada (3%), the United Kingdom (3%), Italy (2%) and Korea (2%). There was a good representation across years in practice. 82% of the respondents have an Associate or Bachelor’s Degree, and 71% work in a general private practice setting. During the pandemic, 52% of respondents are not working at all, 20% are providing restricted in-office treatment (non-aerosol producing) and 15% are providing normal in-office treatment. 14% of the respondents are receiving no compensation, while 86% are receiving compensation from the government and/or their employer. Responses regarding personal protective equipment (PPE) and other protective measures suggest their is a PPE shortage. Gloves (86%), face shields (76%) and surgical masks (69%) are the most commonly reported PPE. About half of the respondents said they are wearing an N95 respirator, goggles, full gown and/or hairnet. Practices are taking other protective measures, such as cleaning/disinfecting all surfaces in the operatory after treatment (85%) and screening patients for symptoms when they arrive (81%) and by phone when they make their appointment (71%). Preprocedural rinses are being used by 57% of respondents for all procedures, with hydrogen peroxide rinse being the most common. 90% of respondents have not had COVID-19 symptoms or are diagnosed wit hit. 9% had symptoms, but were not tested. Less that 2% were diagnosed with COVID-19, and about half of those diagnoses had symptoms. For the summary with detailed results: see www.ifdh.org We sincerely hope we all can continue our normal life soon, as IFDH continues to focus on our agenda as discussed at our 2020 House of Delegates meeting in Brisbane, including our Global Oral Health Summit and Executive Leadership Forum planned for 2021.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.073 | 0.023 |
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".