MétaCan
Menu
Back to cohort
Record W2159685120

Fecal occult blood testing: people in Ontario are unaware of it and not ready for it.

2009· article· en· W2159685120 on OpenAlexaffabout
Paul Ritvo, Ronald E. Myers, M. Elisabeth Del Giudice, Lawrence Pazsat, Michelle Cotterchio, Roberta I. Howlett, Verna Mai, Patrick A. Brown, Terrence Sullivan, Linda Rabeneck

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsCancer Care Ontario
Fundersnot available
KeywordsFecal occult bloodMedicineOccultFecesGerontologyDemographyFamily medicineAlternative medicineInternal medicineColonoscopyPathologyCancerColorectal cancerBiology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine factors that influence awareness of, and readiness to undergo, fecal occult blood testing (FOBT) for colorectal cancer (CRC) screening. DESIGN: Validated survey designed to ascertain respondents' stages of decision making regarding CRC screening using FOBT. SETTING: Ontario. PARTICIPANTS: A total of 1013 people 50 years old and older drawn from all regions of the province using a random-digit dialing telephone protocol. MAIN OUTCOME MEASURES: Awareness of FOBT and readiness to undergo it for screening for CRC. RESULTS: Response rate was 69%. Results indicated that 54% of women and 45% of men had "heard of" FOBT, and 26% of women and 17% of men had heard of it but were still "not considering" FOBT screening. Only 17% of all respondents had "decided to have" FOBT screening. Demographic factors associated with having heard of FOBT were female sex, completion of college or higher education, and being married or living as married. Demographic factors associated with active consideration of FOBT among those who reported awareness of it were male sex and being married or living as married. CONCLUSION: Many people seemed uninformed about FOBT and not ready to undertake this type of screening. Results of this survey could help guide strategies and develop programs to make eligible people aware of CRC screening using FOBT and to motivate them to undergo testing.

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)0.001
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 score0.160
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.081
GPT teacher head0.272
Teacher spread0.191 · 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

Citations16
Published2009
Admission routes2
Has abstractyes

Explore more

Same venuePubMedSame topicColorectal Cancer Screening and DetectionFrench-language works237,207