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Record W2796791113 · doi:10.1177/1534735418762496

Cancer and Complementary Therapies: Current Trends in Survivors’ Interest and Use

2018· article· en· W2796791113 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueIntegrative Cancer Therapies · 2018
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsAlberta Health ServicesUniversity of Calgary
FundersAlberta InnovatesAlberta Innovates - Health SolutionsAlberta Cancer Foundation
KeywordsCancerMedicineCurrent (fluid)OncologyIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Cancer survivors use complementary therapies (CTs) for a variety of reasons; however, with interest and use reportedly on the rise and a widening range of products and practices available, there is a need to establish trends in and drivers of interest. We aimed to determine (1) frequencies of use, level of interest, and barriers for 30 specific CTs and (2) whether physical symptoms, perceived stress (PS), or spiritual well-being were related to interest levels. METHOD: A total of 212 cancer outpatients were surveyed at the Tom Baker Cancer Centre in Calgary, Canada. RESULTS: Overall, up to 75% of survivors already used some form of CTs since their diagnosis. The most highly used were the following: vitamins B12 and D, multivitamins, calcium, and breathing and relaxation exercises. Those who had not used CTs indicated highest interest in massage, vitamin B12, breathing and relaxation, mindfulness-based stress reduction, and antioxidants. The most frequently reported barriers for all CTs were not knowing enough about what a therapy was and not having enough evidence on whether it worked. High PS predicted higher interest for all CTs, but spirituality was not significantly related to any. Physical symptoms, anxiety, and depression were significant predictors of interest for some CTs. CONCLUSION: These findings provide a blueprint for future clinical efficacy trials and highlight the need for clinical practice guidelines.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.126
GPT teacher head0.418
Teacher spread0.292 · 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