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Record W2012655751 · doi:10.1002/hec.1059

Use of primary health care services according to the different degrees of obesity in the Girona Health Region, Spain

2005· article· en· W2012655751 on OpenAlexaboutno aff
Marc Sáez, Carme Saurina, Germà Coenders, Sònia González‐Raya

Bibliographic record

VenueHealth Economics · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
FundersBanco Bilbao Vizcaya Argentaria
KeywordsOverweightPrimary careQuarter (Canadian coin)ObesityPrimary health careHealth carePopulationPublic healthHealth servicesDemographyGerontologyMedicineEnvironmental healthGeographyFamily medicineNursingSociologyEconomicsEconomic growth

Abstract

fetched live from OpenAlex

Our main hypothesis in this paper was that, once controlled for age and gender, the use of primary health care services of people in each of the groups defined by their degree of obesity (i.e. normal weight, overweight and obese) did not correspond to the need for care implied by the level of risk of the group he/she belonged to. This fact could reflect some inequity in the utilisation of such services. Using a survey of the general population from the Girona Health Region, Spain, carried out during the fourth quarter of 2002, we have found that: first, the probability of primary health care use decreased with income for GPs (until 1200 Euro) and increased for specialists (from 1500 Euro). Second, we could conclude by confirming our hypothesis, i.e. there was more probability of obese individuals using general practice care, public in particular, and less probability of them using specialists, private in particular, than the rest of individuals. Third, we conclude that the use of multilevel (also hierarchical or mixed) models could explain most of our original findings in this paper.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.114
GPT teacher head0.289
Teacher spread0.175 · 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

Citations15
Published2005
Admission routes1
Has abstractyes

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