Design and Implementation of Survey Quality Control System for Qatar’s First National Mental Health Survey: Case Study
Notice bibliographique
Résumé
BACKGROUND: All World Mental Health (WMH) Surveys apply high standards of data quality. To date, most of the published quality control (QC) procedures for these surveys were in relation to face-to-face interviews. However, owing to the social restrictions that emerged from the COVID-19 pandemic, telephone interviews are the most effective alternative for conducting complex probability-based large-scale surveys. OBJECTIVE: In this paper, we present the QC system implemented in the WMH Qatar Survey, the first WMH Survey conducted during the COVID-19 pandemic in the Middle East. The objective of the QC process was to acquire high data quality through the reduction of random errors and bias in data collection. METHODS: The QC design and procedures in this study were adapted to the telephone survey mode in response to the COVID-19 pandemic. We focus on the design of the QC indicator system and its implementation, including the investigation process, monitoring interviewers' performance during survey fielding and applying quality-informed interventions. RESULTS: The study team investigated 11,035 flags triggered during the 2 waves of the survey data collection. The most triggered flags were related to short question administration duration and multiple visits to the same survey questions or responses. Live monitoring of the interviews helped in understanding why certain duration-related flags were triggered and the interviewing patterns of the interviewers. Corrective and preventive actions were taken against interviewers' behaviors based on the investigation of triggered flags per interviewer and live call monitoring of interviews. Although, in most cases, the interviewers required refresher training sessions and feedback to improve their performance, several interviewers discontinued work because of low productivity and a high number of triggered flags. CONCLUSIONS: The specific QC procedures implemented in the course of the WMH Qatar Survey were essential for successfully meeting the target number of interviews (N=5000). The QC strategies and the new indicators customized for telephone interviews contributed to the flag investigation and verification process. The QC data presented in this study shed light on the rigorous methods and quality monitoring processes in the course of conducting a large-scale national survey on sensitive topics during the COVID-19 pandemic.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,394 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».