MétaCan
Menu
Back to cohort

Data_Sheet_1_Assessment of Current Mental Health Status in a Population-Based Sample of Canadian Men With and Without a History of Prostate Cancer Diagnosis: An Analysis of the Canadian Longitudinal Study on Aging (CLSA).docx

2020· dataset· en· W6908857511 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueFigshare · 2020
Typedataset
Languageen
FieldEngineering
TopicCivil and Structural Engineering Research
Canadian institutionsnot available
Fundersnot available
KeywordsProstate cancerMental healthDepression (economics)OddsLongitudinal studyEpidemiologyLogistic regressionDistressOdds ratio

Abstract

fetched live from OpenAlex

<p>Background: Small-scale studies indicate an increase in mental health disorders among prostate cancer survivors compared to the general population, but large population-based data assessing this relationship are scarce. The present study examined the prevalence of lifetime history of prostate cancer in a cross-sectional sample of Canadian men and assessed the contribution of lifetime history of a prostate cancer diagnosis, multimorbidity, and current alcohol and smoking status to the association with current mental health outcomes in this population.</p><p>Methods: The analytical sample included 25,183 men (aged 45 to 85 years old), who completed a survey as part of the Canadian Longitudinal Study on Aging (CLSA). The Center for Epidemiological Studies Depression Scale (CES-D10), Kessler's Psychological Distress Scale (K10), and self-reported mental health were mental health outcomes. Multiple logistic regression analyses, and controlling for the complexity of the design and covariates, evaluated the association between prostate cancer survivorship, multimorbidity, alcohol and smoking status, and current mental health outcomes.</p><p>Results: The prevalence of lifetime history of prostate cancer diagnosis in this population-based sample of men was 4% (95% CI: 3.7, 4.4). Our results indicate statistically significantly higher odds of current psychological distress (aOR = 1.52, 95% CI: 1.09, 2.11) and screening positive for depression (aOR = 1.24; 95% CI: 1.02, 1.51) among survivors of prostate cancer, compared to men without a history of prostate cancer diagnosis in demographics controlled analyses. After addition of multimorbidity and substance use, the odds of screening positive for depression among survivors of prostate cancer are 1.32 (95% CI: 1.06, 1.64) higher compared to men who never had a history of prostate cancer diagnosis.</p><p>Interpretation: Patient education and empowerment programs aimed at addressing concerns during the diagnosis and treatment and enhancing survivorship care plans by adding routine screening for mental distress to help survivors overcome poor mental health during the cancer survivorship journey, are warranted.</p>

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.469
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.075
GPT teacher head0.340
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