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Record W4387953152 · doi:10.1016/j.ypmed.2023.107745

Social inequalities in trajectories of contacts with the healthcare system in adolescence and young adulthood

2023· article· en· W4387953152 on OpenAlexaff
Sanne Pagh Møller, Andrea E. Willson, Lau Caspar Thygesen

Bibliographic record

VenuePreventive Medicine · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsWestern University
FundersFaculdade de Ciências da Saúde, Universidade de MacauSyddansk UniversitetHelsefonden
KeywordsMedicineInequalityHealth careSocial inequalityYoung adultHealthcare systemGerontologyEconomic growth

Abstract

fetched live from OpenAlex

BACKGROUND: Understanding of healthcare utilization of different populations is useful for prevention and prioritization of healthcare resources. This study aims to identify populations following different trajectories of contacts with the healthcare system and to describe social inequalities between the groups. METHODS: Individuals born 1980-2000 in Denmark were linked to national registers. Contacts with somatic hospitals, psychiatric hospitals, general practitioners, and redeemed prescriptions were counted for each year between 16 and 37 years of age. Trajectories of contacts with the four dimensions of healthcare use were identified using group-based multi-trajectory modeling. RESULTS: Five trajectory groups were identified. One group had low healthcare utilization over time (12% in women; 27% in men). The largest group had low healthcare utilization but more contacts with especially GP (39% in women; 43% in men). A third group had more contacts with most dimensions of the healthcare system (33% in women; 21% in men). The fourth group had many contacts with especially somatic hospitals and GP (7% in women; 4% in men). The fifth group had many contacts especially to psychiatric hospitals (8% in women; 5% in men). Shorter parental education, parental unemployment, family income below the poverty line, and cohabitation with one or no parent was more frequent in the two high utilization groups compared to the lower utilization groups. CONCLUSION: The observed trajectories of health service use and the social inequalities between trajectory groups highlight that prevention and treatment targeting the entire population will benefit from a complementary focus on social inequalities in health.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.047
GPT teacher head0.361
Teacher spread0.314 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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