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Enregistrement W7105990442 · doi:10.7939/83054

Assessing the Transitional Impact of Adverse Public Events and Associated Mental Health Consequences

2025· dissertation· en· W7105990442 sur OpenAlexaboutno aff

Notice bibliographique

RevueUniversity of Alberta Library · 2025
Typedissertation
Langueen
DomainePsychology
ThématiquePosttraumatic Stress Disorder Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPandemicAffect (linguistics)Natural disasterMental healthPublic healthNatural experimentNatural (archaeology)Psychological distress

Résumé

récupéré en direct d'OpenAlex

Major public events like the COVID-19 pandemic and natural disasters profoundly impact the lives of large groups of people. These events often produce economic hardship, social disruption, and psychological distress that can be long-lasting. Moreover, these events indicate significant changes in people's lives. To elaborate, these calamitous public events can indicate transition– a synchronized, fundamental change in the fabric-of-daily life, in what people do, where they do it, and with whom. Therefore, the aim of the current thesis was to investigate: (a) the nature and extent of the transition caused by COVID-19 pandemic and natural disasters, (b) the impact of the pandemic- or disaster-specific transition, (c) the effect of the pandemic-or-disaster on individuals’ mental-health, and (d) the relationship between the effect of pandemic-or-disaster brought transition and mental-health. This was accomplished in four studies. Chapter 1 provides a general introduction of the potential transitional properties of the pandemic and natural disaster, and how this pandemic- or disaster-related transition can affect the lives and mental-health of individuals. Here, an overview of the research findings related to transition, pandemic, disaster, and mental-health was provided. For simplicity, Chapter 1 is split into two-parts. The first-part discusses the COVID-19 pandemic, and the second-part discusses natural disasters. Chapter 2 (Study-1) reports the results of a cross-sectional survey of Canada-US adults conducted between March 24 and 30, 2020, at the COVID-19 pandemic onset. This study examined the immediate effect of the pandemic-brought transition, pandemic’s impact on mental-health, and the degree to which the two were related. The results indicated that at early stage, the pandemic produced: only moderate material and psychological change, and mild-to-moderate distress; job-loss people experienced more change and more distress than those who did not; material and psychological change were associated with depression and stress while anxiety was associated with only psychological change. Chapter 3 (Study-2) describes the findings of a longitudinal survey of Canada-US and Turkish adults compared across four time-points (March 2020 – April 2022). Study-2 examined the long-term transitional effects brought by the COVID-19 pandemic, its impact on mental-health, and the extent of their association. The results demonstrated that as time progressed, the pandemic: produced only moderate material and psychological change for both groups, although Turkey experienced more changes during the onset while North America experienced more changes later; both groups experienced mild-to-moderate distress while Turkey experienced more distress at the outset than North America; material and psychological changes were reliably associated with distress in North America, whereas in Turkey, only material change was reliably associated with distress. Chapter 4 (Study-3) reports the results of a longitudinal survey of Southern Alberta, Canada residents, who experienced the 2013 flood. This follow-up study was conducted in 2019. It assessed the long-term transitional impacts of the Southern Alberta flood of 2013 and the relationship between this disaster-specific transition and mental-health. The results indicated that respondents reported lower material and psychological change in 2019 than in 2013. After six-years, post-traumatic-stress had a high correlation with material and psychological change; however, depression and anxiety were reliably related to psychological change only. Chapter 5 (Study-4) describes the outcomes of a longitudinal survey of British Columbia, Canada, and Western Germany residents who experienced the 201 wildfire and flood, respectively. Study-4 examined the transitional effect of the BC-fire and Germany-flood, and the associated mental-health consequences, immediately after the disasters and a year later. The results demonstrated that Germany-flood produced higher material and psychological change in 2021 than 2022; BC-fire produced higher psychological change in 2021 than 2022, but produced modest material change in both time-points. Also, the BC-fire group reported greater distress in 2021 than 2022, and the Germany-flood group reported moderate-to-severe distress in both waves; neither group experienced PTSD-like symptoms. Moreover, in both groups, evacuees experienced more change and distress than non-evacuees. Furthermore, over time, only psychological changes were reliably associated with distress in both groups. Chapter 6 provides a general summary of the findings and discusses the importance and implications of short- and long-term life changes brought by calamitic public events (COVID-19 pandemic, natural disasters) and their relationship with mental-health outcomes. Particularly, the present findings highlight the potential to enhance the understanding of long-term recovery needs after a crisis, for both communities and the individuals living within them.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,010
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,021

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,010
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0020,001
Communication savante0,0020,003
Science ouverte0,0010,004
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0050,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,048
Tête enseignante GPT0,361
Écart entre enseignants0,313 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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