Primary care transformation in Scotland: a comparison of two cross-sectional national surveys of GPs’ views in 2018 and 2023
Bibliographic record
Abstract
Background The 2018 Scottish GP contract established GP Clusters and multidisciplinary team (MDT) expansion. Qualitative studies have suggested suboptimal progress with these initiatives. Aim To quantify progress since the introduction of the new contract. Design & setting A cross-sectional postal survey of all qualified GPs was undertaken in Scotland in 2023. Method GPs working lives, career intentions, and views on the new contract were compared with a similar survey conducted in 2018. Results In total, 1385/4529 (31%) GPs responded to the 2023 survey compared with 2465/4371 (56%) in 2018. Job satisfaction and negative job attributes were similar in both surveys. Both positive job attributes ( P = 0.011) and job pressures ( P = 0.004) increased but the changes were small (effect sizes <0.2). Significantly more GPs were planning to reduce hours ( P <0.001) and leave direct patient care ( P = 0.008) in 2023 than in 2018. Quality leads’ views on Cluster working were unchanged, with 70–80% reporting insufficient support. Cluster knowledge and engagement was unchanged but there were small increases in knowledge of quality improvement. More than half of the GPs reported that access to MDT staff was insufficient to reduce their workload in all staff categories except vaccinations. Significantly more practices were trying to recruit GPs ( P <0.01), and GPs reported worsening NHS services, higher workload, and lower practice sustainability in 2023 ( P <0.001). Only 5% of GPs in the 2023 survey thought that the new contract had improved the care of patients with complex needs. Conclusions GPs report few improvements in working life 5 years after the new contract was introduced, and are responding by planning to reduce their hours or leave direct patient care.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".