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Record W2735715450 · doi:10.1080/08870446.2017.1346194

The role of stressful life events on the cortisol reactivity patterns of breast cancer survivors

2017· article· en· W2735715450 on OpenAlexafffund
Cynthia Wan, Marie-Ève Couture-Lalande, Sophie Lebel, Catherine Bielajew

Bibliographic record

VenuePsychology and Health · 2017
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsUniversity of Ottawa
FundersCanadian Breast Cancer Research Alliance
KeywordsTrier social stress testStressorBreast cancerPsychologyCancerSalivaClinical psychologyEndocrine systemInternal medicineOncologyHydrocortisoneMedicinePhysiologyFight-or-flight responseHormone

Abstract

fetched live from OpenAlex

OBJECTIVE: Atypical patterns of cortisol secretion following an acute stressor have been commonly reported in breast cancer survivors. Stressful life events have been associated with blunted acute cortisol levels in other populations. The purpose of this study was to explore the role of stressful life events on cortisol secretion patterns of breast cancer survivors following an acute stressor. DESIGN: The Trier Social Stress (TSST) was used to elicit a moderate stress response in breast cancer survivors (n = 19) and a control group (n = 17). Saliva samples were collected before, during and after the TSST to provide cortisol concentrations. During recovery, we recorded the frequency and subjective impact of stressful life events in the past year using the Life Experience Survey. RESULTS: Simple regressions analyses were performed; results suggest no group differences between the total number of stressful life events and their subjective impact. However, the total number of stressful life events as well as their subjective impact correlated negatively with the peak cortisol concentration in breast cancer survivors. CONCLUSIONS: The cumulative effect of stressful life events, positive and negative, may impact the endocrine stress system of breast cancer survivors more so than that of women with no history of cancer.

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 score0.089
Threshold uncertainty score0.973

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 head0.044
GPT teacher head0.390
Teacher spread0.346 · 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

Citations9
Published2017
Admission routes2
Has abstractyes

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