Health and Well-Being in the Context of Health-Promoting University Initiatives: Protocol for a Mixed Methods Needs Assessment Study at Qatar University
Notice bibliographique
Résumé
BACKGROUND: Health-promoting universities are dedicated to fostering learning environments and organizational cultures that support the physical and mental well-being of students, faculty, and staff. As students constitute the largest group within the university community, any policy intervention targeting them is likely to have a significant impact on the university as a whole. OBJECTIVE: This study aims to assess the health status and needs of Qatar University (QU) students using a comprehensive and holistic definition of health, informed by the perspectives of students, faculty members, and key informants. The ultimate goal is to inform evidence-based policies and services designed to improve students' physical and mental well-being. METHODS: An explanatory sequential mixed-methods research design will be used to conduct a comprehensive assessment of students' health status and needs. This assessment will consist of a quantitative component (a web-based health survey) administered to a convenience sample of students, and a qualitative component, including focus groups with students and faculty members, as well as interviews with key informants. Priority health issues and their determinants, identified through the quantitative assessment, will inform and guide the qualitative assessment to provide a deeper understanding of the various contexts and factors shaping them. Descriptive analyses (eg, proportions or means with SDs), comparative analyses (eg, t tests or chi-square tests), and association analyses (eg, linear, logistic, or Poisson regression models) will be used to analyze the quantitative data. Thematic analysis will be used in the qualitative assessments. Additionally, an environmental scan will be conducted to assess relevant facilities, services, and programs at the QU campus and the QU Primary Healthcare Corporation Center, as well as to review university policies and regulations that may affect students' health and well-being. Together, the needs assessment and environmental scan will inform the design of multilevel interventions, including health education and promotion programs, health services orientation, and proposed policy changes. RESULTS: Between March and December 2022, 812 students completed the web-based health survey. Data have been extracted, cleaned, and harmonized. Analyses to assess the extent of selection bias and the calculation of weights to account for this in all subsequent analyses have been completed (by December 2023). Following the completion of all quantitative data analyses (expected by the end of 2024), focus groups, interviews, and the environmental scan will begin in January-December 2025. CONCLUSIONS: This project will help identify and prioritize the health needs of QU students and their determinants, and inform relevant services and policies targeting these needs. By using comprehensive and context-appropriate methods, this project will contribute to QU's strategic efforts to become a Health-Promoting University. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58860.
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 | 0,069 | 0,036 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,003 |
| Méta-épidémiologie (sens large) | 0,004 | 0,004 |
| Bibliométrie | 0,004 | 0,003 |
| Études des sciences et des technologies | 0,007 | 0,003 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,004 | 0,004 |
| Intégrité de la recherche | 0,006 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,042 | 0,010 |
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 ».