Comparison of the estimated prevalence of mood and/or anxiety disorders in Canada between self-report and administrative data
Notice bibliographique
Résumé
BACKGROUND: To compare trends in the estimated prevalence of mood and/or anxiety disorders identified from two data sources (self-report and administrative). Reviewing, synthesising and interpreting data from these two sources will help identify potential factors that underlie the observed estimates and inform public health action. METHOD: We used self-reported, diagnosed mood and/or anxiety disorder cases from the Canadian Community Health Survey (CCHS) across a 5-year span (from 2003 to 2009) to estimate the prevalence among the Canadian population aged ≥15 years. We also estimated the prevalence of mood and/or anxiety disorders using the Canadian Chronic Disease Surveillance System (CCDSS), which identified cases using ICD-9/-10-CA codes from physician billing claims and hospital discharge records during the same time period. The prevalence rates for mood and/or anxiety disorders were compared across the CCHS and CCDSS by age and sex for all available years of data from 2003 to 2009. Summary rates were age-standardised to the Canadian population as of 1 October 1991. RESULTS: In 2009, the prevalence of mood and/or anxiety disorders was 9.4% using self-reported data v. 11.3% using administrative data. Prevalence rates obtained from administrative data were consistently higher than those from self-report for both men and women. However, due to an increase in the prevalence of self-reported cases, these differences decreased over time (rate ratios for both sexes: 1.6-1.2). Prevalence estimates were consistently higher among females compared with males irrespective of data source. While differences in the prevalence estimates between the two data sources were evident across all age groups, the reduction of these differences was greater among adolescent, young and middle-aged adults compared with those 70 years and older. CONCLUSIONS: The overall narrowing of differences over time reflects a convergence of information regarding the prevalence of mood and/or anxiety disorders trends between self-report and administrative data sources. While the administrative data-based prevalences remained relatively stable, the self-reported prevalences increased over time. These observations may reflect positive societal changes in the perceptions of mental health (declining stigma) and/or increasing mental health literacy. Additional research using non-ecological data is required to further our understanding of the observed findings and trends, including a data linkage exercise permitting a comparison of prevalence estimates and population characteristics from these two data sources both separately and merged.
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 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 | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| 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 ».