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Record W2150546930 · doi:10.1521/psyc.2009.72.4.321

Coping with Early Breast Cancer: Couple Adjustment Processes and Couple-Based Intervention

2009· review· en· W2150546930 on OpenAlexaff
Sandra Naaman, Karam Radwan, Susan M. Johnson

Bibliographic record

VenuePsychiatry · 2009
Typereview
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBreast cancerBiopsychosocial modelCoping (psychology)DistressPsychological interventionSpousePsychotherapistClinical psychologyInterpersonal communicationPsychologyDiseaseInterpersonal relationshipIntervention (counseling)MedicinePsychiatryCancerSocial psychology

Abstract

fetched live from OpenAlex

Early breast cancer affects one in every nine women along with their families. Advances in screening and biomedical interventions have changed the face of breast cancer from a terminal condition to a chronic disease with biopsychosocial features. The present review surveyed the nature and extent of psychological morbidity experienced by the breast cancer survivor and her spouse during the post-treatment phase, with particular focus on the impact of disease on the marital relationship. Interpersonal processes shown to unfold in couples facing breast cancer, as well as risk factors associated with greater psychological morbidity, were reviewed. Moreover, interpersonal processes central to coping with chronic illness and adjustment were reconceptualized from the point of view of attachment theory. Attachment theory was also used as the grounding framework for an empirically supported couples-based intervention, Emotionally Focused Therapy, which is advanced as a potentially useful treatment option for couples experiencing unremitting psychological and relational distress following diagnosis and treatment for breast 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.027
GPT teacher head0.341
Teacher spread0.314 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations75
Published2009
Admission routes1
Has abstractyes

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