Family physician leadership during the COVID-19 pandemic: roles, functions and key supports
Bibliographic record
Abstract
PURPOSE: Strong leadership in primary care is necessary to coordinate an effective pandemic response; however, descriptions of leadership roles for family physicians are absent from previous pandemic plans. This study aims to describe the leadership roles and functions family physicians played during the COVID-19 pandemic in Canada and identify supports and barriers to formalizing these roles in future pandemic plans. DESIGN/METHODOLOGY/APPROACH: This study conducted semi-structured qualitative interviews with family physicians across four regions in Canada as part of a multiple case study. During the interviews, participants were asked about their roles during each pandemic stage and the facilitators and barriers they experienced. Interviews were transcribed and a thematic analysis approach was used to identify recurring themes. FINDINGS: Sixty-eight family physicians completed interviews. Three key functions of family physician leadership during the pandemic were identified: conveying knowledge, developing and adapting protocols for primary care practices and advocacy. Each function involved curating and synthesizing information, tailoring communications based on individual needs and building upon established relationships. PRACTICAL IMPLICATIONS: Findings demonstrate the need for future pandemic plans to incorporate formal family physician leadership appointments, as well as supports such as training, communication aides and compensation to allow family physicians to enact these key roles. ORIGINALITY/VALUE: The COVID-19 pandemic presents a unique opportunity to examine the leadership roles of family physicians, which have been largely overlooked in past pandemic plans. This study's findings highlight the importance of these roles toward delivering an effective and coordinated pandemic response with uninterrupted and safe access to primary 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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".