Evidence map›Paper›PMID 38586382›Full record

ArticleHeliyon2024

Mental health impacts of COVID-19: A retrospective analysis of dynamic modelling projections for Australia.

Adam Skinner, Jo-An Occhipinti, Yun Ju Christine Song, Ian B Hickie

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Adam SkinnerBrain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
Jo-An OcchipintiBrain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
Yun Ju Christine SongBrain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.
Ian B HickieBrain and Mind Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In early 2020, we developed a dynamic model to support policy responses aimed at mitigating the adverse mental health effects of the COVID-19 pandemic in Australia. As the pandemic has progressed, it has become clear that our initial model forecasts overestimated the impacts of infection control measures (lockdowns, physical distancing, etc.) on suicide, intentional self-harm hospitalisation, and mental health-related emergency department (ED) presentation rates. Methods: Potential explanations for the divergence of our model predictions from observed outcomes were assessed by comparing simulation results for a set of progressively more refined models with data on the prevalence of moderate to very high psychological distress and numbers of suicides, intentional self-harm hospitalisations, and mental health-related ED presentations published after our modelling was released in July 2020. Results: Allowing per capita rates of spontaneous recovery and intentional self-harm to differ between people experiencing moderate to very high psychological distress prior to the pandemic and those developing comparable levels of psychological distress only as a consequence of infection control measures substantially improves the fit of our model to empirical estimates of the prevalence of psychological distress and leads to significantly lower predicted effects of COVID-19 on suicide, intentional self-harm hospitalisation, and mental health-related ED presentation rates. Conclusion: Accommodating the influence of prior mental health on the psychological effects of population-wide social and economic disruption is likely to be critical for accurately forecasting the mental health impacts of future public health crises as they inevitably arise.

Indexed as

PandemicPsychological distressSocial disconnectionSuicideSystem dynamicsUnemployment

Identifiers

PMID38586382
PMCPMC10998102

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.