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Record W4387692404 · doi:10.1080/13607863.2023.2268032

The role of positive psychological wellbeing in walking speed differences among married and unmarried English older adults

2023· article· en· W4387692404 on OpenAlexaff
Katherine J. Ford, Rachel J. Burns

Bibliographic record

VenueAging & Mental Health · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsCarleton University
FundersNational Institute on Aging
KeywordsMarital statusPsychologyPreferred walking speedDemographyConfidence intervalGerontologyMedicinePopulationPhysical therapy

Abstract

fetched live from OpenAlex

Objectives: Walking speed has been identified as an important indicator of functional independence and survival among older adults, with marital status being related to walking speed differences. We explored explanatory factors, with a focus on positive psychological wellbeing, in walking speed differences between married and non-married individuals in later life. Methods: We used wave 8 (2016/17) cross-sectional data from adults aged 60–79 years who participated in the English Longitudinal Study of Ageing (n = 3,743). An Oaxaca-Blinder decomposition was used to compute walking speed differences between married and unmarried individuals, and the portion of those differences that could be explained by characteristic differences in those groups, particularly wellbeing. Results: Overall, married individuals had walking speeds that were 0.073 m/s (95% confidence interval: 0.055–0.092 m/s) faster than their unmarried counterparts. This was primarily driven by differences between the married and separated/divorced group, and the widowed group. Included covariates explained roughly 89% of the overall walking speed difference. Positive psychological wellbeing consistently explained a significant portion of walking speed differences, ranging between 7% to 18% across comparisons. Conclusion: Although wealth has been previously found to partially explain walking speed differences by marital status, we found that positive psychological wellbeing also demonstrated pertinence to these differences.

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)0.000
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 score0.054
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.012
GPT teacher head0.330
Teacher spread0.319 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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