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Record W1954493476 · doi:10.1515/jcim-2014-0070

From the conventional to the alternative: exploring patients’ pathways of cancer treatment and care

2015· article· en· W1954493476 on OpenAlex

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

VenueJournal of Complementary and Integrative Medicine · 2015
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsUniversity of TorontoUniversity of Calgary
Fundersnot available
KeywordsMedicineIntegrative medicineHealth careAlternative medicineReceiptProstate cancerBreast cancerCancer treatmentFamily medicineCancer

Abstract

fetched live from OpenAlex

BACKGROUND: Complementary and alternative medicine (CAM) use is widespread and on the increase among cancer patients. Most research to date has involved a cross-sectional snapshot of CAM use rather than an exploration into the longitudinal, nonlinear treatment trajectories that cancer patients develop. Our aim is to explore and describe different treatment and decision-making pathways that individuals develop after receipt of a diagnosis of either breast, colorectal, or prostate cancer. METHODS: The study was part of a larger mixed-methods pilot project to explore the feasibility of conducting a five-year international study to assess cancer patients' treatment pathways, including health care use and the perceived impact of different patterns of use on health outcomes over the course of one year. The results presented in this paper are based on the analysis of personal interviews that were conducted over the course of 12 months with 30 participants. RESULTS: Five pathways emerged from the data: passive conventional, self-directed conventional, cautious integrative, aggressive integrative, and aggressive alternative. Factors that shaped each pathway included health beliefs, decision-making role, illness characteristics, and the patient-practitioner relationship. CONCLUSIONS: The results of this examination of the longitudinal treatment and decision-making trajectory provide important information to support health care professionals in their quest for individualized, targeted support at each stage of the patient pathway.

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)0.000
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 score0.312
Threshold uncertainty score0.310

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.190
GPT teacher head0.380
Teacher spread0.190 · 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