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Record W2737070939 · doi:10.1080/07380577.2017.1337282

Looking Forward and Looking Back: Older Adults' Views of the Impacts of Stopping Driving

2017· article· en· W2737070939 on OpenAlexafffundabout
Nadia Mullen, Barbara Parker, Elaine Wiersma, Arne Stinchcombe, Michel Bédard

Bibliographic record

VenueOccupational Therapy In Health Care · 2017
Typearticle
Languageen
FieldHealth Professions
TopicOlder Adults Driving Studies
Canadian institutionsSt. Joseph's Care GroupLakehead Psychiatric HospitalLakehead University
FundersCanadian Institutes of Health ResearchNorthwestern University
KeywordsPsychological interventionPsychologyFocus groupResistance (ecology)Applied psychologyGerontologyMedicineBusinessPsychiatryMarketing

Abstract

fetched live from OpenAlex

This project aimed to identify the impact of driving cessation from the perspectives of older drivers and former drivers. Participants included 17 adults aged 65-88 years residing in a city in Northwestern Ontario, Canada. Using a semi-structured interview guide (with questions regarding mobility, personal impact, impact on others, engagement with life, and finances), two focus groups were held with nine current drivers, and one-on-one interviews were held with six former drivers and two current drivers. Two themes emerged concerning stopping driving. The first theme included discussions on experiencing lifestyle changes, relationship impacts, and emotional impacts. The second, the adjustment to stopping driving, included practical adaptations, and emotional responses such as appreciation, resistance, acceptance, and being positive. Although the impacts of stopping driving were substantial, there were few discrepancies between what was anticipated and what was experienced. This information could assist with developing interventions to ease the transition to former-driver status.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.042
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.060
GPT teacher head0.439
Teacher spread0.379 · 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

Citations21
Published2017
Admission routes3
Has abstractyes

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