Internet-Based Cognitive Behavioral Therapy for Residual Symptoms in Bipolar Disorder Type II: A Single-Subject Design Pilot Study
Notice bibliographique
Résumé
BACKGROUND: Bipolar disorder is a chronic condition with recurring episodes that often lead to suffering, decreased functioning, and sick leave. Pharmacotherapy in the form of mood stabilizers is widely available, but does not eliminate the risk of a new depressive or (hypo)manic episode. One way to reduce the risk of future episodes is to combine pharmacological treatment with individual or group psychological interventions. However, access to such interventions is often limited due to a shortage of trained therapists. In unipolar depression there is now robust evidence of the effectiveness of Internet-based psychological interventions, usually comprising psychoeducation and cognitive behavioral therapy (CBT). Internet-based interventions for persons suffering from bipolar disorder could increase access to psychological treatment. OBJECTIVE: The aim of this study was to investigate the feasibility of an Internet-based intervention, as well as its effect on residual depressive symptoms in persons diagnosed with bipolar disorder type II (BP-II). The most important outcomes were depressive symptoms, treatment adherence, and whether the patient perceived the intervention as helpful. METHODS: A total of 7 patients diagnosed with bipolar disorder type II at a Swedish psychiatric outpatient clinic were offered the opportunity to participate. Of the 7 patients, 3 (43%) dropped out before treatment began, and 4 (57%) were treated by means of an online, Internet-based intervention based on CBT (iCBT). The intervention was primarily aimed at psychoeducation, treatment of residual depressive symptoms, emotion regulation, and improved sleep. All patients had ongoing pharmacological treatment at recruitment and established contact with a psychiatrist. The duration of BP-II among the treated patients was between 6 and 31 years. A single-subject design was used and the results of the 4 participating patients were presented individually. RESULTS: Initiating treatment was perceived as too demanding under current life circumstances for 3 patients who consequently dropped out during baseline assessment. Self-ratings using the Montgomery-Åsberg Depression Rating Scale-Self-rated (MADRS-S) showed symptom reduction in 3 (75%) of the 4 treated cases during iCBT. In the evaluation of the treatment, 2 patients reported that they perceived that the treatment had reduced symptoms a little, 1 that it had reduced symptoms very much, and 1 not at all. Treatment adherence (ie, module completion) was fairly high in 3 cases. In general, the modules were perceived as fairly helpful or very helpful by the patients. In one case, there was a reliable change-according to the Reliable Change Index-in self-rated symptoms of depression and perseverative thinking. CONCLUSIONS: The treatment seemed to have acceptable feasibility. The iCBT intervention could be an effective way to treat residual symptoms in some patients with bipolar disorder type II. This should be investigated in a larger study. TRIAL REGISTRATION: ClinicalTrials.gov NCT01742351; https://clinicaltrials.gov/ct2/show/NCT01742351 (Archived by WebCite at http://www.webcitation.org/6XnVpv4C3).
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 | 0,004 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».