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Record W7048059208

The Influence of Neighbourhood Deprivation on Health Related Quality of Life In Advanced Arthritis

2016· dissertation· en· W7048059208 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2016
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsNeighbourhood (mathematics)PovertySocioeconomic statusPublic healthSocial deprivationQuality of life (healthcare)Mental healthSocial determinants of health
DOInot available

Abstract

fetched live from OpenAlex

Arthritis is a growing aging and public health concern in Canada and elsewhere. As with many other chronic health conditions, arthritis occurs more often and has a higher impact on functioning for people who have lower incomes or live in an impoverished environment. There is a large body of research that supports a gradient between socioeconomic status and health and between area level poverty and decreased quality of life. Although this relationship is widely acknowledged, less is known about the influence of broader social conditions at the neighbourhood level on health outcomes. By examining quality of life from the theoretical framework of poverty as a fundamental cause of differences in health (Link & Phelan, 1995) and Bourdieu’s (1984) theory of habitus, I provide an analysis of the direct impact of material and social deprivation on health related quality of life (HRQoL), as well as the impact considering the influence of age, body weight, physical functioning, gender, and coexisting health conditions. I also examine interaction effects between neighbourhood deprivation and individual characteristics. An explanatory three-level multilevel model supported a relationship between individual factors as well as deprivation at the neighbourhood level on quality of life. The impact of neighbourhood deprivation was more pronounced for mental health related life quality, with a history of another health condition making the largest contribution to the model. Physical HRQoL was impacted by gender in interaction with material deprivation and body mass index in interaction with social deprivation. I discuss implications for practice, service delivery, and policy and make suggestions for further research.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.208
Threshold uncertainty score0.413

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.250
Teacher spread0.237 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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