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Record W2001071815 · doi:10.1038/sj.bjc.6603086

Psychological effects of a low-grade abnormal cervical smear test result: anxiety and associated factors

2006· article· en· W2001071815 on OpenAlexaff
Nicola Gray, Linda Sharp, Seonaidh Cotton, L. F. Masson, Julian Little, Liz Walker, Mark Avis, Z Philips, Ian Russell, David K. Whynes, Margaret Cruickshank, Claire Woolley

Bibliographic record

VenueBritish Journal of Cancer · 2006
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Ottawa
FundersMedical Research Council
KeywordsAnxietyMedicinePsychosocialPsychological interventionCervical cancerHospital Anxiety and Depression ScaleDepression (economics)PsychiatryClinical psychologyObstetricsCancerInternal medicine

Abstract

fetched live from OpenAlex

Receipt of an abnormal cervical smear result often generates fear and confusion and can have a negative impact on a woman's well-being. Most previous studies have focussed on high-grade abnormal smears. This study describes the psychological and psychosocial effects, on women, of having received a low-grade abnormal smear result. Over 3500 women recruited to TOMBOLA (Trial Of Management of Borderline and Other Low-grade Abnormal smears) participated in this study. Anxiety was assessed using the Hospital Anxiety and Depression Scale (HADS) at recruitment. Socio-demographic and lifestyle factors, locus of control and factors associated with the psychosocial impact of the abnormal smear result were also assessed. Women reported anxiety levels consistent with those found in previous studies of women with high-grade smear results. Women at highest risk of anxiety were younger, had children, were current smokers, or had the highest levels of physical activity. Interventions that focus particularly on women's understanding of smear results and pre-cancer, and/or directly address their fears about cancer, treatment and fertility might provide the greatest opportunity to reduce the adverse psychosocial impact of receiving a low-grade abnormal cervical smear result.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.484

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)0.0000.000

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 head0.009
GPT teacher head0.275
Teacher spread0.266 · 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

Citations105
Published2006
Admission routes1
Has abstractyes

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