Video Consultations in General Practice: Tendencies and Lessons Learned From the First COVID-19 Lockdown Period
Bibliographic record
Abstract
Background Video consultation was urgently introduced in general practice in connection with the COVID-19 pandemic, where a rapid implementation ensured patients’ continued access to their general practitioner (GP). With the Danish lockdown in March 2020, the use of video consultations in general practice increased drastically and then declined significantly shortly after as society gradually reopened. Today, only a small proportion of the total number of consultations in general practice is made up of video consultations, and there is great variation in the scope and use of video consultation among GPs and practice staff. Objective The aim of this paper is to present research findings from a qualitative, interdisciplinary project, investigating GP and patient experiences with video consultations during the first lockdown period in 2020, which might help explain the abovementioned tendencies in relation to scope and implementation variances. Methods The data corpus includes data generated through semistructured interviews with 27 patients and 15 GPs, as well as 8 video recordings of video consultations between GP and patient. Results The patients reported positive experiences with consulting their GP through video, valuing increased convenience and spatial flexibility and wishing for future use of video consultation as either a supplement or an alternative to physical consultation. Video consultation furthermore presented a new communicative context in which both patients and GPs enacted distinct forms of technologically facilitated participation. Conclusions To further the best use of video consultation in future general practice, organizational and individual factors such as renumeration, task delegation, time pressure, and professional identity need to be considered.
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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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".