Does concurrent medication usage affect patient response to internet-delivered cognitive behaviour therapy for depression and anxiety?
Notice bibliographique
Résumé
BACKGROUND: There is growing interest in Internet-delivered cognitive behavioural therapy (ICBT) as an alternative to face-to-face therapy for anxiety and depression because it reduces barriers to accessing traditional treatment (e.g., travel distance, cost, stigma). Extensive research has demonstrated that ICBT is an effective treatment for anxiety and depression and that it produces effect sizes comparable to medication and face-to-face therapy. In routine practice, however, ICBT patients commonly receive simultaneous pharmacological treatment, and few studies have examined how medication affects patient outcomes. OBJECTIVE: The objective of this study was to explore whether use of psychotropic medications predicts outcomes or adherence among patients receiving ICBT for depression and anxiety in a large community sample. METHODS: This study used data from 1201 patients who received an 8-week course of ICBT for anxiety and depression that included weekly therapist support as part of routine care. Patients reported medication usage and completed measures of depression and anxiety before treatment, after treatment, and at three-month follow-up. RESULTS: 60% of patients at pre-treatment reported regularly taking psychotropic medication. Common classes of medication reported included: (i) selective serotonin reuptake inhibitors (34%); (ii) anxiolytics (15%); (iii) serotonin and norepinephrine reuptake inhibitors (14%); (iv) antipsychotics (8%); and (v) norepinephrine-dopamine reuptake inhibitors (7%). At post-treatment and three-month follow-up, overall medication usage reduced slightly to 55%, with the greatest reduction seen in anxiolytics. Logistic regression revealed that none of the classes of medication commonly reported at pre-treatment were associated with study completion rates. A recursive partitioning algorithm found that usage of tetracyclic medication was related to smaller pre-to-post reductions in anxiety symptoms and did not identify any medication types that were related to differences in depressive symptom change. Patients on medication tended to report higher levels of anxiety symptoms at intake and experienced somewhat more modest symptom reductions than patients not taking medications; nevertheless, they still experienced large reductions in depression and anxiety over the course of treatment. CONCLUSIONS: These results show that medication usage is very common in a diverse community sample of patients seeking ICBT for anxiety and depression. Patients reporting medication usage at intake are likely to benefit from treatment approximately as much as patients not taking medication. These results support the continued referral of patients receiving psychotropic medication to ICBT programs for anxiety and depression. Program designers might also consider providing information about the common medications (SSRIs, SNRIs, anxiolytics) used by this population alongside CBT materials.
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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 | 0,002 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».