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Comparisons of depression, anxiety, well-being, and perceptions of the built environment amongst adults seeking social, intermediate and market-rent accommodation in the former London Olympic Athletes’ Village

2017· article· en· W2758182753 on OpenAlexfundno aff
Bina Ram, Aparna Shankar, Claire Nightingale, Billie Giles‐Corti, Anne Ellaway, Ashley R Cooper, Angie S Page, Steven Cummins, Daniel Lewis, Peter H. Whincup, Derek G. Cook, Alicja R. Rudnicka, Christopher G. Owen

Bibliographic record

VenueHealth & Place · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
FundersMedical Research Council CanadaUniversity of SouthamptonMedical Research CouncilUniversity of East AngliaNational Institute for Health and Care Research
KeywordsNeighbourhood (mathematics)HappinessAccommodationAnxietyPsychologyMental healthPerceptionDepression (economics)Demographic economicsGerontologySocial psychologyMedicinePsychiatryEconomics

Abstract

fetched live from OpenAlex

The Examining Neighbourhood Activities in Built Living Environments in London (ENABLE London) study provides a unique opportunity to examine differences in mental health and well-being amongst adults seeking social, intermediate (affordable rent), and market-rent housing in a purpose built neighbourhood (East Village, the former London 2012 Olympic Athletes' Village), specifically designed to encourage positive health behaviours. Multi-level logistic regression models examined baseline differences in levels of depression, anxiety and well-being across the housing groups. Compared with the intermediate group, those seeking social housing were more likely to be depressed, anxious and had poorer well-being after adjustment for demographic and health status variables. Further adjustments for neighbourhood perceptions suggest that compared with the intermediate group, perceived neighbourhood characteristics may be an important determinant of depression amongst those seeking social housing, and lower levels of happiness the previous day amongst those seeking market-rent housing. These findings add to the extensive literature on inequalities in health, and provide a strong basis for future longitudinal work that will examine change in depression, anxiety and well-being after moving into East Village, where those seeking social housing potentially have the most to gain.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.015
GPT teacher head0.316
Teacher spread0.300 · 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 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

Citations11
Published2017
Admission routes1
Has abstractyes

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