General Practitioners’ Experiences of Professional Uncertainties Emerging from the Introduction of Video Consultations in General Practice: Qualitative Study
Bibliographic record
Abstract
BACKGROUND: Uncertainties are omnipresent in health care, but little is known about general practitioners' (GPs) professional uncertainties concerning digital consultations. This is problematic, as many countries have undergone an extensive digital transformation. OBJECTIVE: The aim of this study was to explore the professional uncertainties that emerged among Danish GPs with the introduction of video consultations. METHODS: We conducted qualitative interviews with 15 Danish GPs during the beginning of the COVID-19 pandemic in 2020. The interviews were analyzed using an abductive approach. RESULTS: We identified 3 categories of uncertainty: integrity, setting, and interaction. Respectively, these 3 categories of uncertainty refer to (1) uncertainties related to how technology may impede the provision of health care; (2) uncertainties related to the potentials of video technology; and (3) uncertainties related to how the video consultation technology affects interactions with patients. CONCLUSIONS: The uncertainties experienced by Danish GPs appear to be a typical reaction to the introduction of new technology. Embedding video consultation technology into GPs' working routines will take time, and GPs do not necessarily feel intuitively capable of transferring their abilities, such as being good and socially present for video-mediated consultations. The heterogeneity of professional uncertainties experienced among the GPs suggests that they are the product of individual GP-technology relationships-not of the technology in itself. Consequently, we cannot expect that uncertainties can be remedied by changing or precluding new technology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".