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Record W2134774085 · doi:10.1136/ebn.6.3.95

Patients with cancer often felt a need to conceal their distress to protect family, friends, and doctors

2003· letter· en· W2134774085 on OpenAlexaff
Gladys McPherson

Bibliographic record

VenueEvidence-Based Nursing · 2003
Typeletter
Languageen
FieldMedicine
TopicPalliative Care and End-of-Life Issues
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineGynecologyInternal medicinePediatrics

Abstract

fetched live from OpenAlex

Byrne A, Ellershaw J, Holcombe C, et al. Patients’ experience of cancer: evidence of the role of ‘fighting’ in collusive clinical communication. Patient Educ Couns2002 ; 48 : 15 –21 [OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] QUESTION: How do patients respond to having cancer? Qualitative study. Hospital clinics and a day care at an associated hospice in the UK. 30 patients who were 37–88 years of age (median age 55 y, 60% women, 100% white). Patients had cancer of the breast (n=11), lung (n=4), bowel/anus (n=6), larynx/tonsil/neck (n=3), cervix (n=2), kidney/liver (n=2), and prostate (n=1). 1 patient had non-Hodgkin’s lymphoma. The time since treatment was ≤7 days for 4 patients, <1 year for 14 patients, and 1–19 years for 12 patients. 14 patients received curative treatment and 16 palliative treatment. Patients were individually interviewed for 30–180 minutes (mean 65 min) about their experience of cancer. Open questions, prompts, and reflection were used to help patients describe personal changes and their experiences of others. Interviews were audiotaped and transcribed. An inductive thematic analysis was done. (1) … [1]: {openurl}?query=rft.jtitle%253DPatient%2Beducation%2Band%2Bcounseling%26rft.stitle%253DPatient%2BEduc%2BCouns%26rft.aulast%253DByrne%26rft.auinit1%253DA.%26rft.volume%253D48%26rft.issue%253D1%26rft.spage%253D15%26rft.epage%253D21%26rft.atitle%253DPatients%2527%2Bexperience%2Bof%2Bcancer%253A%2Bevidence%2Bof%2Bthe%2Brole%2Bof%2B%2527fighting%2527%2Bin%2Bcollusive%2Bclinical%2Bcommunication.%26rft_id%253Dinfo%253Adoi%252F10.1016%252FS0738-3991%252802%252900094-0%26rft_id%253Dinfo%253Apmid%252F12220746%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1016/S0738-3991(02)00094-0&link_type=DOI [3]: /lookup/external-ref?access_num=12220746&link_type=MED&atom=%2Febnurs%2F6%2F3%2F95.atom [4]: /lookup/external-ref?access_num=000178953400003&link_type=ISI

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.302
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.104
GPT teacher head0.386
Teacher spread0.281 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations0
Published2003
Admission routes1
Has abstractyes

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