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Record W1755359331 · doi:10.1155/2015/630717

Health Characteristics of Solo Grandparent Caregivers and Single Parents: A Comparative Profile Using the Behavior Risk Factor Surveillance Survey

2015· article· en· W1755359331 on OpenAlexafffund
Deborah M. Whitley, Esme Fuller‐Thomson, Sarah Brennenstuhl

Bibliographic record

VenueCurrent Gerontology and Geriatrics Research · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicIntergenerational Family Dynamics and Caregiving
Canadian institutionsInstitute for Work & HealthUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsGrandparentMedicineRecreationDepression (economics)Risk factorGerontologyDevelopmental psychologyPsychology

Abstract

fetched live from OpenAlex

Objectives. To describe the health characteristics of solo grandparents raising grandchildren compared with single parents. Methods. Using the 2012 Behavioral Risk Factor Surveillance System, respondents identified as a single grandparent raising a grandchild were categorized as a solo grandparent; grandparent responses were compared with single parents. Descriptive analysis compared health characteristics of 925 solo grandparents with 7,786 single parents. Results. Compared to single parents, grandparents have a higher prevalence of physical health problems (e.g., arthritis). Both parent groups have a high prevalence of lifetime depression. A larger share of grandparents actively smoke and did no recreational physical exercise in the last month. However, grandparents appear to have better access to health services in comparison with single parents. Conclusion. Solo grandparents may be at risk for diminished physical capacity and heightened prevalence of depression. Health professionals can be an important resource to increase grandparents' physical and emotional capacities.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.015
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.336
GPT teacher head0.476
Teacher spread0.140 · 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

Citations31
Published2015
Admission routes2
Has abstractyes

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