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Record W2147356156 · doi:10.1002/pon.692

Cancer patients consultation patterns in primary care and levels of psychological morbidity: Findings from the Health Survey for England

2003· article· en· W2147356156 on OpenAlexaboutno aff
Victoria Allgar, Richard D Neal, Shane Pascoe

Bibliographic record

VenuePsycho-Oncology · 2003
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
FundersUniversity of Essex
KeywordsAnxietyDepression (economics)MedicineMental illnessQuarter (Canadian coin)PsychiatryMental healthCancerFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

AIM: To determine the consultations patterns in general practice, for people with cancer and other chronic illnesses, and to assess the levels of psychological morbidity. METHODS: The following questions from the 1999 Health Survey for England were analysed: presence of a self-reported long-standing illness and its nature, numbers of contacts with general practitioner (GP) in the previous 2 weeks, contact with a GP in the previous year for anxiety/depression or a mental, nervous or emotional problem, presence of a self-reported long-standing illness of mental illness, anxiety or depression, and GHQ12 scores. For comparison purposes, data from respondents reporting having asthma, arthritis, diabetes, other long-standing illness, and no long-standing illness are presented. RESULTS: A third of respondents with cancer had contact with a GP in the last 2 weeks, which was slightly higher than the other illness group, however the pattern of attendances for those respondents who did consult were similar between groups. A quarter of people with cancer had spoken to a GP in the last year about being anxious/depressed, or about a mental, nervous or emotional problem. A third of cancer respondents reported high GHQ12 scores, but self-reported long-standing illness of 'mental illness/anxiety/depression' was low (4%). CONCLUSION: The findings suggest that psychological morbidity may be unrecognised in some cancer patients. There is potential for these symptoms to be identified and treated in primary care, especially given the ongoing nature of the patient-doctor relationship and the easy access primary care affords.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.079
GPT teacher head0.397
Teacher spread0.318 · 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 designObservational
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

Citations15
Published2003
Admission routes1
Has abstractyes

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