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Record W2769614416 · doi:10.1177/0733464817741683

The Social Context of Driving Cessation: Understanding the Effects of Cessation on the Life Satisfaction of Older Drivers and Their Social Partners

2017· article· en· W2769614416 on OpenAlexaff
Emily Schryer, Kathrin Boerner, Amy Horowitz, Joann P. Reinhardt, Steven E. Mock

Bibliographic record

VenueJournal of Applied Gerontology · 2017
Typearticle
Languageen
FieldHealth Professions
TopicOlder Adults Driving Studies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsModerationContext (archaeology)Life satisfactionSmoking cessationPsychologySocial environmentGerontologySocial supportEnvironmental healthMedicineSocial psychologySociologyGeography

Abstract

fetched live from OpenAlex

Older adults with vision loss and a friend or family member were interviewed over a 2-year period. We examined the effects of driving cessation on life satisfaction among older adults and a social contact. Drivers' use of public transportation was examined as a moderator. Driving cessation was associated with a decline in life satisfaction among social partners but not for the drivers. Drivers' use of public transportation at baseline moderated the effects of cessation on changes in well-being among social partners, but had little effect on the life satisfaction of the drivers. Life satisfaction was greater among the social partners of ex-drivers who used public transportation more frequently. The association between driving cessation and well-being should be studied in the context of older drivers' social networks. Infrastructure (e.g., subways and buses) that supports transportation needs plays an important role in mitigating the effects of cessation on older adults' social networks.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.488
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
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 head0.090
GPT teacher head0.398
Teacher spread0.308 · 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

Citations17
Published2017
Admission routes1
Has abstractyes

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