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Record W2099732804 · doi:10.1002/cncr.24372

Making a link between childhood physical abuse and cancer

2009· article· en· W2099732804 on OpenAlexaffabout
Esme Fuller‐Thomson, Sarah Brennenstuhl

Bibliographic record

VenueCancer · 2009
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineOdds ratioPhysical abuseSocioeconomic statusConfidence intervalStressorDemographyChild abuseCancerPoison controlOddsInjury preventionGerontologyPsychiatryEnvironmental healthLogistic regressionPopulationInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Abuse in childhood is associated with many negative adult health outcomes. Only 1 study to date has found an association between childhood abuse and cancer. By using a regionally representative community sample, this preliminary study sought to investigate the association between childhood physical abuse and cancer while controlling for 3 clusters of risk factors: childhood stressors, adult health behaviors, and adult socioeconomic status. METHODS: Regional data from the Canadian provinces of Manitoba and Saskatchewan were selected from the 2005 Canadian Community Health Survey. Of the 13,092 respondents, 7.4% (n = 1025) reported that they had been physically abused as a child by someone close to them, and 5.7% (95% confidence interval [CI], 4.9-6.6) reported that they had been diagnosed with cancer by a health professional. The regional level response rate was 84%. RESULTS: Childhood physical abuse was associated with 49% higher odds (95% CI, 1.10-2.01) of cancer when adjusting for age, sex, and race only. The odds ratio decreased only slightly to 47% higher odds (95% CI, 1.05-1.99) when the model was adjusted for all 3 clusters of risk factors. CONCLUSIONS: A significant and highly stable association between childhood physical abuse and cancer was found even when adjusting for 3 clusters of risk factors. Further research focusing on the potential mechanisms linking childhood abuse and cancer is 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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.948
Threshold uncertainty score0.728

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.367
Teacher spread0.326 · 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

Citations118
Published2009
Admission routes2
Has abstractyes

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