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Record W4312000322 · doi:10.3399/bjgpo.2022.0168

Factors affecting patient decisions to undergo testing for cancer symptoms: an exploratory qualitative study in Australian general practice

2022· article· en· W4312000322 on OpenAlexaff
Brent Venning, Rebecca J. Bergin, Alison Pearce, Alex Lee, Jon Emery

Bibliographic record

VenueBJGP Open · 2022
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsOccupational Cancer Research Centre
FundersRoyal Australian College of General PractitionersRACGP FoundationCancer Research UK
KeywordsWorryThematic analysisMedicineQualitative researchExploratory researchTest (biology)Family medicineCancerGeneral practiceNursingPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Patients presenting to their GP are often concerned their symptoms may be due to cancer. However, there is a lack of evidence on the factors that influence patient decisions to undergo investigation for suspected cancer in the general practice setting. AIM: To identify the factors influencing patient decisions to undertake investigations for suspected cancer in general practice. DESIGN & SETTING: An exploratory qualitative, semi-structured interview study of patients attending rural and metropolitan general practices in Victoria, Australia. METHOD: A purposive sample of 15 general practice patients aged ≥40 years participated. Thematic analysis of transcripts drew on interpretative description methodology and shared decision-making (SDM) theory. RESULTS: Cancer-related concerns such as 'cancer worry' prompt patients to seek investigations from their GP. Participants prefer that their symptoms are investigated regardless of cancer risk. The perceived 'best test' provides the most reassurance. Trust and SDM enhance dialogue between patients and GPs about diagnostic testing strategies. Deterrents to testing included out-of-pocket costs, waiting time, travel time, and competing work and family demands. CONCLUSION: There may be a mismatch between efforts to rationalise investigation use and patient preferences for investigation. SDM that incorporates patient concerns, facilitators, and barriers to testing may ensure appropriate and timely investigation of cancer symptoms.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.486
GPT teacher head0.537
Teacher spread0.051 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2022
Admission routes1
Has abstractyes

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