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Record W1599524404 · doi:10.1080/07347331003678352

Self-Efficacy, Perceived Preparedness, and Psychological Distress in Women Completing Primary Treatment for Breast Cancer

2010· article· en· W1599524404 on OpenAlexaff
Jennifer M. Jones, Terry Cheng, Maureen Jackman, Gary Rodin, Tara Walton, Pamela Catton

Bibliographic record

VenueJournal of Psychosocial Oncology · 2010
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsDistressClinical psychologyMoodPreparednessBreast cancerSelf-efficacyMedicinePsychological interventionPsychologyPsychiatryCancerInternal medicinePsychotherapist

Abstract

fetched live from OpenAlex

The present analyses were conducted to examine demographic and clinical variables associated with mood and health-related distress in a sample of 440 women completing primary treatment for early-stage breast cancer. The authors' aim was to test the hypothesis that higher levels of self-efficacy and perceived preparedness for the end of treatment--the reentry phase--are associated with better mood and lower health-related distress in this sample. Women who had received chemotherapy and who were younger (<50 years) had significantly higher mood disturbance and health-related distress scores. Younger age, preparedness, and self-efficacy predicted 36% of the variance in mood disturbance scores. Self-efficacy and age predicted 26% of the variance in health-related distress. Although further research is needed, our findings suggest that self-efficacy and perceived preparedness represent important constructs to target in the development of interventions for women at the reentry transition.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.813
Threshold uncertainty score0.463

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.032
GPT teacher head0.378
Teacher spread0.347 · 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

Citations32
Published2010
Admission routes1
Has abstractyes

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