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Record W3142481231 · doi:10.1177/0898264321997715

The Factors Associated with 3-Year Mortality Stratified by Physical and Mental Multimorbidity and Area of Residence Deprivation in Primary Care Community-Living Older Adults

2021· article· en· W3142481231 on OpenAlexaff
Helen‐Maria Vasiliadis, Samantha Gontijo Guerra, Djamal Berbiche, Isabelle Pitrou

Bibliographic record

VenueJournal of Aging and Health · 2021
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsHôpital Charles-Le MoyneUniversité de Sherbrooke
Fundersnot available
KeywordsSocioeconomic statusMedicineResidenceGerontologyMental healthSocial supportDemographyPublic healthStratified samplingEnvironmental healthPopulationPsychologyPsychiatryNursing

Abstract

fetched live from OpenAlex

Objectives: To examine the risk factors of mortality stratified by physical and mental multimorbidity (PMM) and area socioeconomic status. Methods: Cox regression analyses were used to study 3-year all-cause mortality in primary care older adults stratified by PMM status, and area of residence material and social deprivation. Results: There were socioeconomic differences in the associations between PMM and mortality. Continuity of care decreased mortality risk in moderately and most deprived areas. Satisfaction with medical consultations decreased mortality risk in moderately deprived areas. Current smoking increased mortality in those living in moderately and most deprived areas. Physical activity reduced mortality only in individuals without PMM. Higher cognition was associated with reduced mortality in individuals living in moderately deprived areas. Discussion: Public health policies should be further encouraged in primary care, aiming at increased continuity of care, quality of interactions with patients, and prevention strategies including smoking cessation programs and physical activity promotion.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.021
Threshold uncertainty score0.169

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.062
GPT teacher head0.349
Teacher spread0.288 · 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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