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Is the association between psychological distress and risky alcohol consumption shifting over time? An age-period-cohort analysis of the Australian population

2023· article· en· W4384942526 on OpenAlexfundno aff
Jillian Halladay, Tim Slade, Cath Chapman, Louise Mewton, Siobhan O’Dean, Rachel Visontay, Andrew Baillie, Maree Teesson, Matthew Sunderland

Bibliographic record

VenuePsychiatry Research · 2023
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsDemographyCohortDistressAlcohol consumptionPopulationMedicineCohort studyPsychological distressCohort effectPsychologyPsychiatryAlcoholClinical psychologyEnvironmental healthMental healthInternal medicine

Abstract

fetched live from OpenAlex

This study explored age, period, and cohort effects associated with trends in psychological distress and risky alcohol consumption. Data came from 108,536 Australians aged 14-79 years old from birth cohorts between 1925-2005, endorsing past year alcohol use in the 2004-2019 Australian National Drug Strategy Household Surveys. Risky alcohol consumption was split into exceeding weekly national drinking limits (>10 drinks per week) or daily limits (>4 drinks per day). An extended hierarchical age-period-cohort model was used to investigate differential effects on trends in psychological distress. Psychological distress showed an inverse U-shape throughout the lifespan with a peak in distress at age 60. Exceeding weekly alcohol limits was positively related to psychological distress prior to age 40 while exceeding daily alcohol limits remained positively related across the lifespan. There were relatively flat period effects, with no alcohol-related changes in psychological distress across years. Lastly, psychological distress gradually increased across birth cohorts until a notable spike among Australians born from 1980-2005 alongside weakening alcohol-related cohort effects. Overall, the recent increases in psychological distress did not appear to be meaningfully explained by risky alcohol consumption though risky alcohol consumption remained an important factor to consider alongside psychological distress.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.222
GPT teacher head0.538
Teacher spread0.316 · 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.

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

Citations18
Published2023
Admission routes1
Has abstractyes

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