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Record W2340499198 · doi:10.1177/0091415016641686

A Lifecourse Model of Multimorbidity Resilience

2016· review· en· W2340499198 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe International Journal of Aging and Human Development · 2016
Typereview
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsSt. Paul's HospitalSimon Fraser University
Fundersnot available
KeywordsResilience (materials science)MultimorbidityPsychologyQuality of life (healthcare)Face (sociological concept)Psychological resilienceGerontologyMedicineSociologySocial psychologyPsychotherapistPsychiatryComorbiditySocial science

Abstract

fetched live from OpenAlex

The purpose of this article is to advance a Lifecourse Model of Multimorbidity Resilience. It focuses on the ways in which individuals face adversities associated with multimorbidity and regain a sense of wellness through a complex, dynamic phenomenon termed resilience. A comprehensive review of 112 publications (between 1995 and 2015) was conducted using several comprehensive electronic data bases. Two independent researchers extracted and synthesized resilience literature with specific applications to chronic illness. The article outlines five stages of theoretical development of resilience, synthesizes these with the aging and chronic illness literature, builds a rationale for a lifecourse approach to resilience, and applies the model to multimorbidity. Cultivating and maintaining resilience is fundamental to functioning and quality of life for those with multimorbidity. We found that there are a number of gaps in both basic and applied research that need to be filled to advance knowledge and practice based on resilience approaches.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.121
GPT teacher head0.410
Teacher spread0.289 · 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