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Record W7095827419

Support Care Cancer (2006) 14: 1077–1085 DOI 10.1007/s00520-006-0088-8 SUPPORTIVE CARE INTERNATIONAL

2006· article· en· W7095827419 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Financial Impacts of Cancer
Canadian institutionsnot available
Fundersnot available
KeywordsCancerWork (physics)Sample (material)Cancer treatmentMEDLINE
DOInot available

Abstract

fetched live from OpenAlex

Financial and family burden associated with cancer treatment in Ontario, Canada Abstract Goals of work: To deter-mine the financial and family resources burden associated with the treatment of cancer. A questionnaire was developed to determine the direct monthly “out-of-pocket costs” (OOPC), the indirect costs, and the associated perceived family burden. Materials and methods: A self-ad-ministered questionnaire using a quota sample from five cancer clinics in Ontario, Canada was given to 282 cancer patients (74 breast, 70 colorectal, 68 lung, and 70 prostate). Monthly OOPC were obtained for: drugs, home care, homemaking, complementary and alternative medicines, vitamins and supplements, family care, travel, parking, accom-modations, devices, and others. The questionnaire asked if OOPC for treatment were a burden, and if others took time from work to provide caregiving. Main results: The mean monthly OOPC was $213, with an additional $372 related to imputed travel costs. For those patients who responded that the burden was “sig-nificant ” (16.5%), their OOPC was $452. In the case of patients re-sponding that their burden was “unmanageable ” (3.9%), their OOPC was $544. The survey showed that 35.6 % of patients required others to take time from work and this was higher in the under-65 category. The mean number of days lost from work in the previous 30 days for these caregivers was 7 days. Conclusions: These results suggest the financial burden is problematic for 20 % of this sample. The caregivers ’ lost time from work influence this burden, and for 36 % of this sample, it amounts to one third of their working days in any given month. Policies and programs to address these gaps are needed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.291
Threshold uncertainty score0.973

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2910.048

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 head0.014
GPT teacher head0.236
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2006
Admission routes1
Has abstractyes

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