MétaCan
Menu
Back to cohort
Record W2604288445 · doi:10.1159/000468923

Associations between Pain and Quality of Life in Severe Dementia: A Norwegian Cross-Sectional Study

2017· article· en· W2604288445 on OpenAlexaff
Hanne Marie Rostad, Martine Puts, Milada Cvancarova Småstuen, Ellen Karine Grov, Inger Utne, Liv Halvorsrud

Bibliographic record

VenueDementia and Geriatric Cognitive Disorders Extra · 2017
Typearticle
Languageen
FieldMedicine
TopicPain Management and Opioid Use
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsQuality of life (healthcare)DementiaNorwegianMedicineCross-sectional studyDepressive symptomsPsychological interventionActivities of daily livingPopulationGerontologyPsychiatryPhysical therapyClinical psychologyCognitionDiseaseEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: Many variables influence the quality of life in older adults with dementia. We aim to quantify how the relationship between pain and quality of life in nursing home residents with severe dementia can be explained by neuropsychiatric symptoms, depressive symptoms, and activities of daily living. METHODS: This article presents cross-sectional baseline data from a cluster randomised controlled trial. RESULTS: The total and direct effects of pain on quality of life were statistically significant. Both neuropsychiatric and depressive symptoms partially mediated the relationship between pain and quality of life. Activities of daily living acted as a mediator only when modelled together with depressive symptoms. CONCLUSION: Pain, neuropsychiatric symptoms, and depressive symptoms appear to be important factors that influence the quality of life for nursing home residents with severe dementia. Therefore, multidimensional interventions may be beneficial for maintaining or improving quality of life in this population.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.328
Teacher spread0.296 · 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 source (direct Gemma or distilled Codex), 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

Citations35
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueDementia and Geriatric Cognitive Disorders ExtraSame topicPain Management and Opioid UseFrench-language works237,207