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Record W3193736377 · doi:10.32920/ryerson.14657682.v1

The role of hope in patients' use of cancer-related coping strategies

2021· preprint· en· W3193736377 on OpenAlexaff
Jenna J Belanger

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsToronto Metropolitan UniversitySystems, Applications & Products in Data Processing (Canada)
Fundersnot available
KeywordsCoping (psychology)HarmPsychologyClinical psychologyCoping behaviorDiseaseMedicineSocial psychologyInternal medicine

Abstract

fetched live from OpenAlex

Cancer patient's initial appraisal of the disease (i.e., as a threat, harm, or challenge), as well as their level of hope, has been linked to patients' coping strategies (i.e. approach or avoidance coping). However, it is unclear whether the well-established relationship between primary appraisals and coping in moderated by cancer patients' levels of hope. To determine if hope moderated this realationship, colorectal cancer patients (N=122) completed measures of appraisals and hope following their diagnosis and a measure of coping six-months later. Results indicated that patients appraised cancer as more of a challenge than a threat reported high levels of baseline hope. both challenge appraisals and baseline higher hope predicted approach coming six months later, however, hope did not moderate the relationship between appraisals and coping. This study highlights may of the conceptual, design, and psychometric problems present when measuring appraisals, hope, and coping among cancer patients.

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)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.016
GPT teacher head0.297
Teacher spread0.282 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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