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Record W7103650814 · doi:10.18103/mra.v13i10.6976

Chronic pain can compromise sleep and quality of life in the older.

2025· article· W7103650814 on OpenAlexaff

Bibliographic record

VenueMedical Research Archives · 2025
Typearticle
Language
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversité du Québec à Chicoutimi
FundersUniversidade do Estado da Bahia
KeywordsChronic painPittsburgh Sleep Quality IndexQuality of life (healthcare)Sleep (system call)Analysis of varianceCorrelationSleep qualitySpearman's rank correlation coefficient

Abstract

fetched live from OpenAlex

Background: Age-related changes often disrupt sleep patterns, impacting overall health and quality of life, potentially leading to various health issues and societal challenges due to associated comorbidities and sleep deficiencies. Aim: Test the association of chronic pain with the quality of sleep and health-related quality of life of older. Methods: Clinical, anthropometric data, Pittsburgh Sleep Quality Index; Visual analogue scale; cognitive impairment; World Health Organization Quality of Life-OLD and functional mobility was verified. The means between the groups were compared using the Student's t test for independent samples, Spearman correlation coefficient (ρ) to test the associations and one-way analysis of variance to compare the means between the three age groups. Results: Were involved 131 older, predominantly female (87%), average age 68 ± 7 years. There was a moderate (ρ = 0.590) and significant (p <0.01) positive correlation between Pittsburgh Sleep Quality Index scores and chronic pain intensity and a negative moderate (ρ = - 0.57) and significant (p <0.01) correlation between quality of life and chronic pain.

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)0.020
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.007
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.055
GPT teacher head0.425
Teacher spread0.370 · 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
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
Published2025
Admission routes1
Has abstractyes

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