A longitudinal mixed methods examination of stress during the COVID-19 pandemic in a Canadian sample
Notice bibliographique
Résumé
Background: Stress is a universal experience, which has been exacerbated for many during the COVID-19 pandemic. The overarching goal of this work was to examine the experiences of stress among Canadians over a one-year period during the COVID-19 pandemic. Within this, I aimed to qualitatively understand the greatest stressors Canadians were experiencing at each time point and contextualize their experiences longitudinally. I also aimed to quantitatively understand the prevalence of stress at each time point and over time. Lastly, I used a mixed methods approach to gain a rich understanding of the main stressors qualitatively identified by participants across all time points. Methods: The COVID Survey Canada data were collected between May 2020 and July 2021. Participants (N = 1,074) were recruited via social media platforms and were invited to complete an online baseline survey and two follow-up surveys at six months (n = 484) and one-year (n = 406) following their initial survey completion. I used an exploratory sequential mixed methods approach for data analysis, where I first analyzed the open-ended responses to, “what are you most stressed/concerned about right now?” using reflexive thematic analysis (Braun & Clarke, 2006; 2019; 2023 for three time points individually, and then completed a qualitative longitudinal analysis using interpretative phenomenological analysis (Smith & Osborn, 2007). I quantitatively analyzed the prevalence of both perceived stress and COVID stress at each time point. Guided by the qualitative longitudinal framework, I chose several variables that mapped on to the qualitative longitudinal framework (COVID impact, income change, job loss, and social support) and completed descriptive analyses to provide the prevalence for each variable at all time points. Results: Participants qualitatively identified many stressors at each time point, and five main themes were identified in the longitudinal qualitative framework: the impact of COVID-19, health and wellbeing, economic instability, social connection, and pandemic related guidelines and restrictions. Quantitative analyses supported qualitative findings and demonstrated high rates of perceived stress across each time points, with the highest level of perceived stress at time 1 (76.4%, 71.5%, and 71.5%, respectively). Discussion: These findings highlight the difficult experiences many Canadians went through during COVID-19 and can be used to inform policies, supports, and interventions for both current Canadians experiencing chronic stress due to COVID as well as for future pandemic supports and interventions.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,014 | 0,014 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,006 |
| Études des sciences et des technologies | 0,014 | 0,002 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».