Healthcare Provider Perspectives on Bipolar I Disorder Screening and the Rapid Mood Screener (RMS), a Pragmatic, New Tool
Notice bibliographique
Résumé
Abstract Introduction Although mania is the hallmark symptom of bipolar I disorder (BD-I), most patients initially present for treatment with depressive symptoms. Misdiagnosis of BD-I as major depressive disorder (MDD) is common, potentially resulting in poor outcomes and inappropriate antidepressant monotherapy treatment. Screening patients with depressive symptoms is a practical strategy to help healthcare providers (HCPs) identify when additional assessment for BD-I is warranted. The new 6-item Rapid Mood Screener (RMS) is a pragmatic patient-reported BD-I screening tool that relies on easily understood terminology to screen for manic symptoms and other BD-I features in <2 minutes. The RMS was validated in an observational study in patients with clinically confirmed BD-I (n=67) or MDD (n=72). When 4 or more items were endorsed (“yes”), the sensitivity of the RMS for identifying patients with BP-I was 0.88 and specificity was 0.80; positive and negative predictive values were 0.80 and 0.88, respectively. To more thoroughly understand screening tool use among HCPs, a 10-minute survey was conducted. Methods A nationwide sample of HCPs (N=200) was selected using multiple HCP panels; HCPs were asked to describe their opinions/current use of screening tools, assess the RMS, and evaluate the RMS versus the widely recognized Mood Disorder Questionnaire (MDQ). Results were reported by grouped specialties (primary care physicians, general nurse practitioners [NPs]/physician assistants [PAs], psychiatrists, and psychiatric NPs/PAs). Included HCPs were in practice <30 years, spent at least 75% of their time in clinical practice, saw at least 10 patients with depression per month, and diagnosed MDD or BD in at least 1 patient per month. Findings were reported using descriptive statistics; statistical significance was reported at the 95% confidence interval. Results Among HCPs, 82% used a tool to screen for MDD, while 32% used a tool for BD. Screening tool attributes considered to be of the greatest value included sensitivity (68%), easy to answer questions (66%), specificity (65%), confidence in results (64%), and practicality (62%). Of HCPs familiar with screening tools, 70% thought the RMS was at least somewhat better than other screening tools. Most HCPs were aware of the MDQ (85%), but only 29% reported current use. Most HCPs (81%) preferred the RMS to the MDQ, and the RMS significantly outperformed the MDQ across valued attributes; 76% reported that they were likely to use the RMS to screen new patients with depressive symptoms. A total of 84% said the RMS would have a positive impact on their practice, with 46% saying they would screen more patients for bipolar disorder. Discussion The RMS was viewed positively by HCPs who participated in a brief survey. A large percentage of respondents preferred the RMS over the MDQ and indicated that they would use it in their practice. Collectively, responses indicated that the RMS is likely to have a positive impact on screening behavior. Funding AbbVie Inc.
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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 | 0,000 | 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 | 0,000 |
| 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) | 0,001 | 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.
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