Assessing Physicians and other Healthcare Professionals' Awareness of Language Resources and the Feasibility of Setting up a Volunteer Second Language Database at a Family Health Team and Outpatient Clinic
Bibliographic record
Abstract
Objectives: 1) To assess the awareness of healthcare professionals in resources available to assist patients encounters challenged by language barriers, 2) To explore the feasibility of implementing a voluntary Second Language Database (SLD) comprising of the outpatient clinic’s very own physicians and healthcare professionals to assist with patient encounters facing language barriers. Methods: This was a feasibility study (cross-sectional design), taking place at the Stonechurch Family Health Centre (SFHC), which is a family health team (FHT) located in Hamilton, Ontario. SFHC has a patient population of over 17,000 patients. All personnel at the SFHC were invited to complete the survey from December 2010 to March 2011. Those surveyed included staff physicians, residents, allied healthcare professionals and administrative staff. The outcome measures included: participant demographics, frequency and percentages of patients encounters with language barriers, healthcare professionals’ awareness of available interpretive resources, ability of the participant to communicate in additional languages, participants’ willingness to enlist for a SLD to provide interpretive assistance during patient encounters. Results: Of the 100 participants invited to take part in the survey, 67 completed it (67% response rate). Of the physicians who completed the survey, 94.6% reported having encountered language barriers during patient encounter within the past 12 months. Additionally, 71.1% of physicians surveyed were unaware of any available resources. The majority of physicians (86.8%) thought a SLD would be helpful, and 66% of doctors able to speak a second language were willing to take part in the SLD to assist colleagues in linguistic encounters. All of the surveyed International Medical Graduates/Doctors (IMGs/IMDs) (N=6), knew a second language, with 4 being fluent in additional languages. All of the surveyed IMG’s were willing to volunteer for the SLD. Conclusions: To our knowledge, this is the first study to specifically explore the physicians’ ability and will ingness to volunteer and assist colleagues in linguistic encounters. Physicians were largely unaware of the available resources to overcome patient encounters with language barriers. Given the frequency of healthcare professionals possessing a second language and their willingness to take part in a SLD at outpatient clinics and FHT settings, this may indeed be a feasible proposal to address patient linguistic barriers. IMGs/ IMDs tend to possess multiple languages and may have had previous experience interacting with patients in languages other than English. This, along with their willingness to assist colleagues during such patient encounters enables them to serve as a vital resource for Canadians with language barriers.
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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 | 0.017 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".