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Evidence of recall bias in volunteered vs. prompted responses about occupational exposures

2000· article· en· W2097932899 on OpenAlexaff
Kay Teschke, Joanna Smith, Andrew F. Olshan

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsUniversity of British Columbia
FundersNational Cancer Institute
KeywordsRecall biasMedicineRecallOdds ratioPopulationInformation biasCase-control studyEnvironmental healthDemographySelection biasInternal medicinePsychologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Recall bias remains a concern in case-control studies, although few investigations have found evidence of differential recall. This study examined whether differences in occupational exposure reporting occur in volunteered vs. prompted questionnaire responses. METHODS: In a large, population-based, case-control study of a childhood cancer, neuroblastoma, we calculated odds ratios for broad occupational exposure groups on the assumption that in the absence of recall bias, risk estimates for such broad groupings should be close to the null value. RESULTS: Prompted exposures and work activities showed little evidence of differential recall by parents of cases and controls (all OR < 1.2), but case parents were more likely to volunteer information about other exposures or activities (ORs: 1.35-1.71). Case mothers were also more likely than control mothers to report activities involving indirect exposure (OR = 1.41). CONCLUSIONS: These findings suggest that prompted exposure questions are less likely to be subject to recall bias than open-ended questions.

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)0.138
metaresearch head score (Gemma)0.351
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.730

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1380.351
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.002
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.001
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 head0.129
GPT teacher head0.347
Teacher spread0.218 · 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.

Study designObservational
DomainMethods
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

Citations58
Published2000
Admission routes1
Has abstractyes

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