MétaCan
Menu
Back to cohort
Record W2107434170 · doi:10.1093/geronb/62.4.p226

Does Greater Frequency of Contact With General Physicians Reduce Feelings of Mastery in Older Adults?

2007· article· en· W2107434170 on OpenAlexaff
John Cairney, Laurie Corna, Terrance J. Wade, David L. Streiner

Bibliographic record

VenueThe Journals of Gerontology Series B · 2007
Typearticle
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsFeelingTest (biology)Longitudinal studyPsychologyCross-sectional studyRegression analysisHealth careMedicineGerontologySocial psychology

Abstract

fetched live from OpenAlex

In this study, we test one aspect of Rodin's hypothesis concerning age-related decline in mastery: The effect of frequent contact with the health care sector on mastery. We conducted cross-sectional and longitudinal multiple regression analyses to examine the effect of general physician (GP) visits on mastery. In the cross-sectional analyses, a higher number of GP visits is associated with lower mastery, but this relationship is substantially weakened when physical health is entered into the analysis. These results are confirmed in the longitudinal analysis. The effect of GP visits on mastery thus appears to be significantly confounded by physical health problems. These findings direct attention away from the role of contact with the health care sector in influencing perceived mastery and toward the importance of physical health status as both a cause and potential consequence of changes in perceived control with age.

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)0.006
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.349
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 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

Citations12
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueThe Journals of Gerontology Series BSame topicAging and Gerontology ResearchFrench-language works237,207