Drug Attitude, Insight, and Patient’s Knowledge About Prescribed Antipsychotics in Schizophrenia: A Cross-Sectional Survey
Notice bibliographique
Résumé
Nobuhiro Nagai, 1–3 Hideaki Tani, 1, 4 Kazunari Yoshida, 1, 5 Philip Gerretsen, 6, 7 Takefumi Suzuki, 8 Saeko Ikai-Tani, 1, 9 Masaru Mimura, 1 Hiroyuki Uchida 1 1Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan; 2Department of Psychiatry, Minami-Hanno Hospital, Saitama, Japan; 3Department of Psychiatry, Tokyo-Kaido Hospital, Tokyo, Japan; 4Kimel Family Translational Imaging-Genetics Laboratory, Centre for Addiction and Mental Health, Toronto, ON, Canada; 5Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; 6Multimodal Imaging Group - Research Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada; 7Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, ON, Canada; 8Department of Neuropsychiatry, University of Yamanashi Faculty of Medicine, Yamanashi, Japan; 9Physical Activity and Mental Health, Faculty of Kinesiology & Physical Education, University of Toronto, Toronto, ON, CanadaCorrespondence: Hiroyuki UchidaDepartment of Neuropsychiatry, Keio University School of Medicine, 35, Shinanomachi, Shinjuku-Ku, Tokyo 160-8582, JapanTel +81353633829Fax +81353790187Email hiroyuki.uchida.hu@gmail.comIntroduction: While patients’ perspectives toward pharmacotherapy are expected to be directly influenced by their motivation and understanding of the treatment that they are currently receiving, no study has comprehensively investigated the impact of insight into illness and knowledge for the ongoing pharmacotherapy on the attitude towards drug treatment among patients with schizophrenia.Materials and Methods: One hundred forty-eight Japanese outpatients diagnosed with schizophrenia, according to the International Classification of Diseases 10th edition, were included (mean±SD age, 47.3± 12.4 years; 90 men (60.8%)). Attitudes toward antipsychotic treatment and insight into illness were assessed with the Drug Attitude Inventory-10 (DAI-10) and the VAGUS, respectively. In addition, a multiple-choice questionnaire that was designed to examine patients’ knowledge about therapeutic effects, types, and implicated neurotransmitters of antipsychotic drugs they were receiving was utilized.Results: The mean±SD of DAI-10 score was 4.7± 4.2. The multiple regression analysis found that lower Positive and Negative Syndrome Scale (PANSS) scores, higher VAGUS scores, and longer illness duration were significantly associated with higher DAI-10 scores (β=− 0.226, P=0.009; β=0.250, P=0.008; β=0.203, P=0.034, respectively). There was a significant difference in the DAI-10 scores between the subjects who gave more accurate answers regarding the effects of their primary antipsychotic and those who did not (mean±SD, 5.57± 4.38 vs 4.13± 4.04, P=0.043); however, this finding failed to survive the multiple regression analysis.Conclusion: Better insight into illness and treatment, lower illness severity, longer illness duration, and possibly greater knowledge about the therapeutic effects of medications may lead to better attitudes towards pharmacotherapy among patients with schizophrenia, which has an important implication for this typically chronic mental condition requiring long-term antipsychotic treatment to sustain stability.Keywords: drug attitude, adherence, insight, knowledge, schizophrenia, antipsychotic\n
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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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».