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Record W4309812305 · doi:10.1016/j.psycom.2022.100092

History of trauma and COVID-19-related psychological distress and PTSD

2022· article· en· W4309812305 on OpenAlexaffabout
Martine Hébert, Arianne Jean-Thorn, Laurie Fortin

Bibliographic record

VenuePsychiatry Research Communications · 2022
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsDistressPsychological resilienceVulnerability (computing)Psychological distressPandemicCoronavirus disease 2019 (COVID-19)Clinical psychologyPsychiatryPsychologyYoung adultMedicineAnxietyDevelopmental psychologyPsychotherapistInternal medicine

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has a great impact on society as a whole. Yet the pandemic and associated mandatory lockdown in several countries may have increased the vulnerability of certain populations. The present study aimed to document the frequency of clinical level of psychological distress and COVID-19 related post-traumatic stress symptoms in youth during the first wave of the pandemic. The study more specifically explored the role of prior trauma and adverse life events as a vulnerability factor for negative outcomes. A sample of 4914 adolescents and young adults from the province of Quebec, Canada was recruited online through social networks during the first wave of COVID-19. Results revealed that 26.6% of youth displayed serious psychological distress and 20.3% probable PTSD symptoms. The number of past traumas and adversity experienced showed a dose-response relation with the prevalence of psychological distress and PTSD. After controlling for socio-demographic characteristics and COVID-19 related variables (exposure, fear, suspicion of having the infection), participants with a history of five traumas and more presented a two-fold risk of serious psychological distress and probable PTSD. Emotion dysregulation was also associated with an increased risk of symptoms while resilience was linked to a reduced risk of 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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.519
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0020.002
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.317
GPT teacher head0.509
Teacher spread0.192 · 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 designTheoretical or conceptual
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

Citations7
Published2022
Admission routes2
Has abstractyes

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