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Record W1930800226 · doi:10.1002/pon.3932

Androgen deprivation therapy's impact on the mood of prostate cancer patients as perceived by patients and the partners of patients

2015· article· en· W1930800226 on OpenAlexafffund
Dexter Van Dam, Richard J. Wassersug, Lisa Dawn Hamilton

Bibliographic record

VenuePsycho-Oncology · 2015
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of British ColumbiaMount Allison University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMoodAndrogen deprivation therapyProstate cancerAffect (linguistics)MedicineQuality of life (healthcare)Clinical psychologySexual functionInternal medicinePsychologyOncologyPsychotherapistCancer

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the relationship between of androgen deprivation therapy (ADT) and the mood of prostate cancer (PCa) patients and partners of PCa patients. METHODS: PCa patients (n = 295) and partners of patients (n = 84) completed an online survey assessing the patients' current mood and mood prior to treatment, relationship adjustment, and sexual function. We compared men on ADT to men who received non-hormonal treatments for their PCa. RESULTS: Patients currently treated with ADT (n = 82) reported worsened mood as measured by the Profile of Mood States compared to those not on ADT (n = 213). The negative impact of ADT on mood, however, was reduced in older patients. Partners of patients on ADT (n = 42) reported similar declines in the patient's mood that patients reported, but to a greater degree than patient-reported levels. CONCLUSIONS: Our data support ADT's impact on PCa patients' mood and verify that partners concurrently see the effects. The psychological changes related to ADT can impact relationships and affect the quality of life of both PCa patients and partners. Patients and their partners are likely to benefit from being well informed about the psychological effects of androgen deprivation on men beginning ADT. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

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 score0.027
Threshold uncertainty score0.344

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 head0.026
GPT teacher head0.353
Teacher spread0.327 · 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

Citations16
Published2015
Admission routes2
Has abstractyes

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