“Family doctors are also people”: a qualitative analysis of how family physicians managed competing personal and professional responsibilities during the COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: Family physicians (FPs) fill an essential role in public health emergencies yet have frequently been neglected in pandemic response plans. This exclusion harms FPs in their clinical roles and has unintended consequences in the management of concurrent personal responsibilities, many of which were amplified by the pandemic. The objective of our study was to explore the experiences of FPs during the first year of the COVID-19 pandemic to better understand how they managed their competing professional and personal priorities. METHODS: We conducted semi-structured interviews with FPs from four Canadian regions between October 2020 and June 2021. Employing a maximum variation sampling approach, we recruited participants until we achieved saturation. Interviews explored FPs' personal and professional roles and responsibilities during the pandemic, the facilitators and barriers that they encountered, and any gender-related experiences. Transcribed interviews were thematically analysed. RESULTS: We interviewed 68 FPs during the pandemic and identified four overarching themes in participants' discussion of their personal experiences: personal caregiving responsibilities, COVID-19 risk navigation to protect family members, personal health concerns, and available and desired personal supports for FPs to manage their competing responsibilities. While FPs expressed a variety of ways in which their personal experiences made their professional responsibilities more complicated, rarely did that affect the extent to which they participated in the pandemic response. CONCLUSIONS: For FPs to contribute fully to a pandemic response, they must be factored into pandemic plans. Failure to appreciate their unique role and circumstances often leaves FPs feeling unsupported in both their professional and personal lives. Comprehensive planning in anticipation of future pandemics must consider FPs' varied responsibilities, health concerns, and necessary precautions. Having adequate personal and practice supports in place will facilitate the essential role of FPs in responding to a pandemic crisis while continuing to support their patients' primary care needs.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.014 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".