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Record W4401518013 · doi:10.1038/s41598-024-68027-0

A longitudinal study on impact of emergency cash transfer payments during the COVID pandemic on coping among Australian young adults

2024· article· en· W4401518013 on OpenAlexaff
Md Irteja Islam, Elizabeth Lyne, Joseph Freeman, Alexandra Martiniuk

Bibliographic record

VenueScientific Reports · 2024
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsPublic Health OntarioUniversity of Toronto
FundersUniversity of Sydney
KeywordsCoping (psychology)AnxietyPandemicLongitudinal studyMedicineMental healthPsychiatryPsychologyCoronavirus disease 2019 (COVID-19)Disease

Abstract

fetched live from OpenAlex

The coronavirus (COVID-19) pandemic has caused financial hardship and psychological distress among young Australians. This study investigates whether the Australian Government's emergency cash transfer payments-specifically welfare expansion for those unemployed prior to the pandemic (known in Australia as the Coronavirus Supplement) and JobKeeper (cash support for those with reduced or stopped employment due to the pandemic)-were associated with individual's level of coping during the coronavirus pandemic among those with and without mental disorders (including anxiety, depression, ADHD and autism). The sample included 902 young adults who participated in all of the last three waves (8, 9C1, 9C2) of the Longitudinal Study of Australian Children (LSAC), a nationally representative cohort study. Modified Poisson regression models were used to assess the impact of emergency cash transfer payments on 18-22-year-old's self-rated coping level, stratifying the analysis by those with and without mental disorders. All models were adjusted for gender, employment, location, family cohesion, history of smoking, alcohol intake, and COVID-19 test result. Of the 902-person sample analysed, 41.5% (n = 374) reported high levels of coping, 18.9% (n = 171) reported mental disorders, 40.3% (n = 364) received the Coronavirus Supplement and 16.4% (n = 148) received JobKeeper payments. Analysing the total sample demonstrated that participants who received the JobKeeper payment were more likely to have a higher level of coping compared to those who did not receive the JobKeeper payment. Stratified analyses demonstrated that those with pre-existing mental disorder obtained significant benefit from the JobKeeper payment on their level of coping, compared to those who did not receive JobKeeper. In contrast, receipt of the Coronavirus Supplement was not significantly associated with higher level of coping. Among those with no mental health disorder, neither the Coronavirus Supplement nor JobKeeper had a statistically significant impact on level of coping. These findings suggest the positive impacts of cash transfers on level of coping during the pandemic were limited to those with a pre-existing mental disorder who received JobKeeper.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.105
GPT teacher head0.440
Teacher spread0.335 · 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

Labeled directly by 2 models reading the full record.

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

Citations2
Published2024
Admission routes1
Has abstractyes

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