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Record W4385852450 · doi:10.1177/08982643231195924

Perceptions of Increases in Cost of Living and Psychological Distress Among Older Adults

2023· article· en· W4385852450 on OpenAlexafffund
Alex Bierman, Laura Upenieks, Yeonjung Lee

Bibliographic record

VenueJournal of Aging and Health · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Literacy, Pension, Retirement Analysis
Canadian institutionsUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAngerAnxietyPsychologyDistressClinical psychologyDepression (economics)PerceptionMental healthPsychological distressPsychiatry

Abstract

fetched live from OpenAlex

Objectives: This article examines whether older adults’ perceptions of an increase in their cost of living during a time of rapid inflation are associated with multiple aspects of psychological distress, as well as whether mastery buffers these associations. Methods: Data were derived from a two-wave longitudinal survey of older adults gathered in 2021 and 2022 ( N = 4,010). Multiple regression models examined symptoms of depression, anxiety, and anger. Results: Perceptions of moderate or large increases in cost of living were associated with higher levels of distress at follow-up. Taking baseline financial strain, mastery, and psychological distress into account weakened these associations, but perceptions of a large increase in cost of living were still substantially linked with anger and anxiety. Mastery also buffered associations with anxiety and anger. Discussion: Macroeconomically derived adversities can shape anxiety and anger in later-life, but these mental health consequences fall more heavily on individuals possessing lower levels of mastery.

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 score0.004
Threshold uncertainty score0.300

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.318
Teacher spread0.290 · 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

Citations8
Published2023
Admission routes2
Has abstractyes

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