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Record W2088810754 · doi:10.1016/j.ijid.2008.05.445

Prostatitis-like Symptoms: Prevalence and Impact on Quality of Life in Kenyan Youth Aged 16–19 Years

2008· article· en· W2088810754 on OpenAlexaff
Jennifer Pikard

Bibliographic record

VenueInternational Journal of Infectious Diseases · 2008
Typearticle
Languageen
FieldMedicine
TopicHepatitis Viruses Studies and Epidemiology
Canadian institutionsQueen's University
Fundersnot available
KeywordsProstatitisMedicineQuality of life (healthcare)UrinationPhysical therapyKenyaUrinary systemInternal medicineProstate

Abstract

fetched live from OpenAlex

This study examined the prevalence of chronic prostatitis-like symptoms and quality of life (QoL) in community dwelling Kenyan youth aged 16–19 years (n = 166) using the National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI). Prostatitis symptom impact on QoL was examined using pain and urinary symptoms as well as depressive symptoms (Patient Health Questionnaire; PHQ) and demographic information. All participants were registered and attending secondary school during the time of survey. The mean age of the sample was 16.97 (SD = .88). Approximately 23.5% pubertal males reported having total pain domain scores of 4 or greater. Using a prostatitis-like symptom case identification the sample prevalence was 13.3% and 9% using a conservative estimate removing males endorsing pain or burning during urination as a potential indicator of STIs. Further, 5.4% of the sample reported moderate to severe prostatitis symptoms which was reduced to 2.4% when urination pain is removed. Multiple regression analysis showed that school district (β = .20), depressive symptoms (β = .18) and pain (β = .36) predicted poorer QoL and that urinary symptoms did not (β = .11). These findings are discussed in light of the current prevalence data, clinical implications and future research.

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)0.003
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 score0.009
Threshold uncertainty score0.346

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
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 head0.036
GPT teacher head0.352
Teacher spread0.316 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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