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Record W2915226187 · doi:10.28991/esj-2019-01168

Loneliness in Pre and Post-operative Cancer Patients: A Mini Review

2019· review· en· W2915226187 on OpenAlexaff
Ami Rokach

Bibliographic record

VenueEmerging Science Journal · 2019
Typereview
Languageen
FieldHealth Professions
TopicHealth, psychology, and well-being
Canadian institutionsYork University
Fundersnot available
KeywordsLonelinessSocial isolationMedicineIsolation (microbiology)DementiaPsychiatry

Abstract

fetched live from OpenAlex

This review explored the experience of hospitalization and the experience of cancer patients who were undergoing Ear Nose and Throat [ENT] surgery. Hospitals, which were designed with treatment and healing in mind, are known to be the source of uncontrollable noise, physicians who talk in a language that patients do not understand. Entering the hospital as a patient, one becomes part of that very complex system, which may include being treated as a ‘nonperson,' not getting enough information, and losing control of daily activities. Hospitalized patients' social contact is limited to interaction with the medical staff which thus become a key factor in determining the quality of care, and whether the patients can successfully cope with the stress of their hospitalization experience.Loneliness was found to be associated with a range of negative physical health outcomes such as dementia, increased blood pressure, suicidal thinking and unhealthy and damaging behaviors such as smoking, excess alcohol consumption and lack of exercise leading and contributing to increased mortality. Being, both, hospitalized and in the midst of a frightening illness they experience loneliness and isolation.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.953
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.003
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 head0.103
GPT teacher head0.560
Teacher spread0.457 · 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 designOther design
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

Citations11
Published2019
Admission routes1
Has abstractyes

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