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Record W4246445667 · doi:10.32920/ryerson.14661564

The relationship between chronic stress, emotion regulation and depressive symptoms in healthy older adults

2021· preprint· en· W4246445667 on OpenAlexaff
Vivian Huang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAllostatic loadDepressive symptomsChronic stressClinical psychologyAssociation (psychology)PsychologyStress (linguistics)MedicineGerontologyPsychiatryInternal medicineCognition

Abstract

fetched live from OpenAlex

The current study examined the association between chronic stress (measured in allostatic load or AL), ER, and depressive symptoms in a group of community-dwelling older adults. It was hypothesized that chronic stress levels would mediate the relationship between ER and depressive symptoms. A total of 70 older adults aged 60 and older participated in the study. There were no significant associations found in the main analyses between the AL index and depressive symptoms, as well as no significant relationship was found between ER strategies and AL index, after controlling for age, sex, education, and perceived SES. However, perceived stress significantly mediated the relationship between maladaptive ER strategies and depressive symptoms, and the relationship between adaptive ER strategies and depressive symptoms. Given the small sample size and the lack of variability of the AL index, the study would benefit from a larger sample size to clarify the present results.

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)0.002
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0000.000
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 head0.049
GPT teacher head0.382
Teacher spread0.333 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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