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Record W2029228851 · doi:10.1080/07347332.2013.855962

Social Support and Adjustment Among Wives of Men with Prostate Cancer

2013· article· en· W2029228851 on OpenAlexaff
Benjamin H. Gottlieb, Scott B. Maitland, Jamie Brown

Bibliographic record

VenueJournal of Psychosocial Oncology · 2013
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsSocial supportCognitive dissonancePsychologyCoping (psychology)Mental healthPerceptionClinical psychologyProstate cancerEmotional supportSocial psychologyPsychotherapistCancerMedicine

Abstract

fetched live from OpenAlex

This study aims to understand how wives' mental health and life enjoyment are affected by their perceptions of the sufficiency of the support they render to their husbands who have prostate cancer. Its specific purpose is to determine whether these outcomes accrue more strongly to wives who perceive their husbands coping in avoidant ways. Drawing on data from an interview study of 51 wives of men diagnosed with prostate cancer, the authors employ heiarchical regression analysis to examine the wives' adjustment in relation to their provision of support to their husbands. Our findings reveal a significant moderating effect of the husbands' avoidant coping; consistent with cognitive dissonance theory, wives who provided sufficient support to more avoidant husbands demonstrated better mental health and life enjoyment than wives of men who were less avoidant. In addition, the perceived sufficiency of the support provided by the wives' social networks had a stronger bearing on their adjustment than the support provided by their husbands. These findings add to our understanding of the psychological benefits that support providers derive when they communicate support in ways that suit the recipient's style of managing threat.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score1.000

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)0.0010.000

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 head0.019
GPT teacher head0.408
Teacher spread0.389 · 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.

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

Citations7
Published2013
Admission routes1
Has abstractyes

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