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Record W4414722832 · doi:10.3399/bjgpo.2025.0069

English general practice in a period of change: a mixed-methods study of staff and patient perspectives

2025· article· en· W4414722832 on OpenAlex
Heather Gage, Alice Herron, Amanda Bates, R. Michael Cassidy, Catherine Marchand, Emily McKean, Karen Spilsbury, Suzanne H Richards, Rupa Chilvers, Mark Joy, Simon de Lusignan, Stephen Peckham

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBJGP Open · 2025
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsToronto Metropolitan UniversityHealth Sciences Centre
FundersDepartment of Health and Social CareNational Institute for Health and Care Research
KeywordsReceptionistsPeriod (music)General practiceWork (physics)Training (meteorology)

Abstract

fetched live from OpenAlex

BACKGROUND: The COVID-19 pandemic prompted widespread use of remote (telephone and online) communication in general practice in England, which exacerbated long-term pressures from staffing shortages. The public perceived problems with access. AIM: To explore patient and staff perspectives on changing processes in general practice. DESIGN & SETTING: A mixed-methods study (patient survey and staff focus groups) in a sample of 22 general practices in England, varied by size, region, deprivation, and demography, was conducted in 2022. METHOD: An online survey was delivered by short message service (SMS) text to adult patients at 21 practices. Data from answers to an open-ended question about patients' experiences were analysed using summative content and thematic analysis. Virtual focus groups conducted with four categories of staff (GPs, nurses, receptionists and administrators, and practice managers) covered teamworking, roles, patient interactions, adapting to change, and workload. Data were transcribed and analysed using framework and thematic methods. Themes common to patients and staff were identified. RESULTS: Overall median survey response was 10.9% (interquartile range 9.7%-14.6%); 14 401 patient responders provided 10 348 comments, 51.2% were positive. Patient and staff perspectives overlapped in two areas. The first, 'contact and communication', encapsulated differing views around access. The second, 'non-clinical roles and patient care', concerned the allocation of appointments and the roles of receptionists. Patients reported barriers to getting timely appointments with their chosen professional while staff were seeking ways to manage the volume of communications. Use of non-clinical staff to triage appointment requests was unpopular with patients and receptionists felt clinically unqualified. CONCLUSION: Effective methods are needed to improve patient communication with practices and access. Receptionists require recognition and training for their pivotal role.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.534
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.056
GPT teacher head0.477
Teacher spread0.421 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it