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Record W2020136986 · doi:10.1111/phn.12013

Sexually Transmitted Disease Testing Misconceptions Threaten the Validity of Self‐Reported Testing History

2012· article· en· W2020136986 on OpenAlexaboutno aff
Heather Royer, Elizabeth C. Falk, Susan M. Heidrich

Bibliographic record

VenuePublic Health Nursing · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsnot available
Fundersnot available
KeywordsGonorrheaMedicineSexually transmitted diseasePublic healthChlamydiaFamily medicineTest (biology)FeelingQuarter (Canadian coin)GerontologyPsychologyNursingSocial psychologySyphilis

Abstract

fetched live from OpenAlex

OBJECTIVE: Sexually transmitted disease (STD) testing is fundamental to STD prevention and control. We sought to comprehensively examine young women's beliefs about the STD testing process. DESIGN AND SAMPLE: Descriptive, cross-sectional, survey investigation. Women aged 18-24 (n = 302) drawn from four women's health clinics and one university classroom. MEASURES: Participants completed the RoTEST, which measures five domains of women's STD testing beliefs and a demographic survey. RESULTS: Many women believed they would be screened for all STDs when they receive STD testing (40%) and that visual inspection by a provider was a valid method of STD screening for gonorrhea (35%), chlamydia (32%) and HSV (77%). More than a quarter believed that a Pap test screens for gonorrhea (23%) and chlamydia (26%). Twenty-one percent reported that discussing STD testing with a provider is difficult and most reported feeling more comfortable seeking STD testing from an STD specialist rather than a family doctor (79%). CONCLUSIONS: Young women have numerous misconceptions about the STD testing process that may interfere with the validity of their self-reported STD testing history and subsequently undermine public health efforts to improve STD prevention and control. Innovative approaches to educating women about the testing process are 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)0.004
metaresearch head score (Gemma)0.004
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 score0.310
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.270
GPT teacher head0.381
Teacher spread0.111 · 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

Citations15
Published2012
Admission routes1
Has abstractyes

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