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Record W3081387366 · doi:10.5430/jnep.v10n12p38

Adult cancer patients’ barriers toward pain management: A literature review

2020· review· en· W3081387366 on OpenAlexvenueno aff
Hodan Ibrahim, Fadi Khraim, Atef Al-Tawafsheh

Bibliographic record

VenueJournal of Nursing Education and Practice · 2020
Typereview
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsnot available
Fundersnot available
KeywordsCINAHLCancer painMedicineMEDLINEAnxietyFatalismAromatherapyCancerAddictionPain managementThematic analysisClinical psychologyPsychiatryAlternative medicinePhysical therapyQualitative researchPsychological interventionInternal medicine

Abstract

fetched live from OpenAlex

Background and objective: Cancer pain is the most common symptom among cancer patients. Despite strategies to control cancer pain, cancer patients’ beliefs and attitudes influence the effectiveness of cancer pain management. The aim of this literature review was to identify and explore adult cancer patients’ barriers toward pain management.Methods: A literature review was conducted. CINAHL, Medline, and PsychINFO databases were searched for relevant articles from 2008 to 2019. Twenty one articles were included in this literature review. Thematic analysis was conducted to identify and explore adult cancer patients’ barriers toward pain management. Results: This literature review revealed several patient barriers toward pain management. These barriers were categorized into cognitive barriers that include poor pain communication, fatalism, and fear of addiction and tolerance; sensory barrier, such as fear of drug side effects; affective barriers, such as anxiety and depression, and socio-demographic barriers that influence cancer pain management.Conclusions: Adult cancer patients’ barriers toward pain management significantly compromise the effectiveness of pain management and affect cancer patients’ quality of life. A better understanding of cancer patients’ barriers toward pain management by the healthcare providers will result in better assessment and management of these barriers and will enhance evidenced-based patient education.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation 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 score0.706
Threshold uncertainty score0.744

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.056
GPT teacher head0.434
Teacher spread0.379 · 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.

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

Citations4
Published2020
Admission routes1
Has abstractyes

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