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Record W2732167319 · doi:10.1097/spc.0000000000000288

Current directions in research and treatment of fear of cancer recurrence

2017· review· en· W2732167319 on OpenAlexaboutno aff
Louise Sharpe, Belinda Thewes, Phyllis Butow

Bibliographic record

VenueCurrent Opinion in Supportive and Palliative Care · 2017
Typereview
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePsychological interventionIntensive care medicineKey (lock)Clinical trialRisk analysis (engineering)Computer scienceNursingPathology

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: An expert meeting in Ottawa in 2015 galvanized efforts to answer key questions relevant to the understanding and management of fear of cancer recurrence (FCR). The aim of this review is to summarize key developments. RECENT FINDINGS: A consensus on the definition of FCR has helped to further research in this area. There have been a number of theories put forward to account for the development of FCR, all of which share key components. Importantly, a number of important trials have been published that confirm both brief and more intensive interventions can successfully treat FCR. SUMMARY: The consensus definition of FCR is an important development, as is the development of treatments for FCR. There are now evidence-based options for the management of patients with clinical levels of FCR. Future research priorities include determining the optimal cut-off points for identifying clinically significant FCR, testing the major tenets of the recent theoretical formulations of FCR; and determining the relative efficacy and cost-effectiveness of different treatment approaches for managing FCR.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.872
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.558
GPT teacher head0.590
Teacher spread0.032 · 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 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

Citations37
Published2017
Admission routes1
Has abstractyes

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