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Record W3164875624 · doi:10.1002/ejp.1809

Pain evaluation and prosocial behaviour are affected by age and sex

2021· article· en· W3164875624 on OpenAlexaff
Chloé Gingras, Michel‐Pierre Coll, Marie‐Hélène Tessier, Pascale Tremblay, Philip L. Jackson

Bibliographic record

VenueEuropean Journal of Pain · 2021
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsMcGill UniversityUniversité LavalCentre for Interdisciplinary Research in Rehabilitation
Fundersnot available
KeywordsProsocial behaviorEmpathyPsychologyTraitPain catastrophizingPain assessmentClinical psychologyChronic painMedicinePain managementPhysical therapyDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Pain assessment and pain care are influenced by the characteristics of both the patient and the caregiver. Some studies suggest that the pain of older persons and of females may be underestimated to a greater extent than the pain of younger and male individuals. AIMS: This study investigated the effect of age and sex on prosocial behavior and pain evaluation. METHODS: 40 young (18-30 y/o; 20 women) and 40 older adults (55-82 y/o; 20 women) acted as healthcare professionals rating the pain and offering help to patients of both age groups. Trait empathy and social desirability were measured with questionnaires. RESULTS: Linear mixed models showed that older and male patients were offered more help and were perceived as being in more intense pain than younger and female patients. CONCLUSION: The characteristics of the patients seem to have a greater impact on prosocial behavior and pain assessment compared to those of the observers, which bears significant implications for the treatment of pain in clinical contexts.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.461
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
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)0.0000.000

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 head0.020
GPT teacher head0.274
Teacher spread0.253 · 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 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
Published2021
Admission routes1
Has abstractyes

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