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Confidence in Healthcare System vs Life Satisfaction

2023· preprint· en· W4328129483 on OpenAlexaff
Chun Yee Chau

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicPsychological Well-being and Life Satisfaction
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsModerationHealth carePsychologyHealthcare systemPatient satisfactionLife satisfactionConfidence intervalSocial psychologyNursingMedicinePolitical science

Abstract

fetched live from OpenAlex

A large body of research has connected life satisfaction with health. However, there is a lack of research on the relationship between life satisfaction and one’s confidence level in the healthcare system. In this study, the main hypothesis was that these two variables are positively correlated. Also, it was hypothesized that satisfaction with personal health would serve as a moderator. By adopting the data from Gallup World Poll obtained in the year 2009, a multi-level model was conducted. The model was used to predict life satisfaction from confidence in the healthcare system, adjusting for income. Results significantly supported the main hypothesis, showing that individuals’ life satisfaction are likely to be higher when they have higher confidence in healthcare. However, the results did not support the hypothesis of the moderator, meaning that satisfaction with personal health does not moderate the relationship. The results findings could be used to encourage policymakers and healthcare providers to take measures in improving citizens’ confidence level in the healthcare system.

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)0.003
metaresearch head score (Gemma)0.016
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 score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.001

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 head0.087
GPT teacher head0.376
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

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
Published2023
Admission routes1
Has abstractyes

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