Mental health in the pandemic: a repeated cross-sectional mixed-method study protocol to investigate the mental health impacts of the coronavirus pandemic in the UK
Notice bibliographique
Résumé
INTRODUCTION: The WHO declared a global pandemic on 11 March 2020. Since then, the world has been firmly in the grip of the COVID-19. To date, more than 211 730 035 million confirmed cases and more than 4 430 697 million people have died. While controlling the virus and implementing vaccines are the main priorities, the population mental health impacts of the pandemic are expected to be longer term and are less obvious than the physical health ones. Lockdown restrictions, physical distancing, social isolation, as well as the loss of a loved one, working in a frontline capacity and loss of economic security may have negative effects on and increase the mental health challenges in populations around the world. There is a major demand for long-term research examining the mental health experiences and needs of people in order to design adequate policies and interventions for sustained action to respond to individual and population mental health needs both during and after the pandemic. METHODS AND ANALYSIS: This repeated cross-sectional mixed-method study conducts regular self-administered representative surveys, and targeted focus groups and semi-structured interviews with adults in the UK, as well as validation of gathered evidence through citizens' juries for contextualisation (for the UK as a whole and for its four devolved nations) to ensure that emerging mental health problems are identified early on and are properly understood, and that appropriate policies and interventions are developed and implemented across the UK and within devolved contexts. STATA and NVIVO will be used to carry out quantitative and qualitative analysis, respectively. ETHICS AND DISSEMINATION: Ethics approval for this study has been granted by the Cambridge Psychology Research Ethics Committee of the University of Cambridge, UK (PRE 2020.050) and by the Health and Life Sciences Research Ethics Committee of De Montfort University, UK (REF 422991). While unlikely, participants completing the self-administered surveys or participating in the virtual focus groups, semi-structured interviews and citizens' juries might experience distress triggered by questions or conversations. However, appropriate mitigating measures have been adopted and signposting to services and helplines will be available at all times. Furthermore, a dedicated member of staff will also be at hand to debrief following participation in the research and personalised thank-you notes will be sent to everyone taking part in the qualitative research.Study findings will be disseminated in scientific journals, at research conferences, local research symposia and seminars. Evidence-based open access briefings, articles and reports will be available on our study website for everyone to access. Rapid policy briefings targeting issues emerging from the data will also be disseminated to inform policy and practice. These briefings will position the findings within UK public policy and devolved nations policy and socioeconomic contexts in order to develop specific, timely policy recommendations. Additional dissemination will be done through traditional and social media. Our data will be contextualised in view of existing policies, and changes over time as-and-when policies change.
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 | 0,032 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,003 |
| Méta-épidémiologie (sens large) | 0,003 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,026 | 0,006 |
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 ».