Using the Personalized Advantage Index for Individual Treatment Allocation to Blended Treatment or Treatment as Usual for Depression in Secondary Care.
Bayesian model averaging
CBT
blended treatment
depression
personalized advantage index
treatment selection
Journal
Journal of clinical medicine
ISSN: 2077-0383
Titre abrégé: J Clin Med
Pays: Switzerland
ID NLM: 101606588
Informations de publication
Date de publication:
11 Feb 2020
11 Feb 2020
Historique:
received:
30
12
2019
revised:
04
02
2020
accepted:
05
02
2020
entrez:
15
2
2020
pubmed:
15
2
2020
medline:
15
2
2020
Statut:
epublish
Résumé
A variety of effective psychotherapies for depression are available, but patients who suffer from depression vary in their treatment response. Combining face-to-face therapies with internet-based elements in the sense of blended treatment is a new approach to treatment for depression. The goal of this study was to answer the following research questions: (1) What are the most important predictors determining optimal treatment allocation to treatment as usual or blended treatment? and (2) Would model-determined treatment allocation using this predictive information and the personalized advantage index (PAI)-approach result in better treatment outcomes? Bayesian model averaging (BMA) was applied to the data of a randomized controlled trial (RCT) comparing the efficacy of treatment as usual and blended treatment in depressive outpatients. Pre-treatment symptomatology and treatment expectancy predicted outcomes irrespective of treatment condition, whereas different prescriptive predictors were found. A PAI of 2.33 PHQ-9 points was found, meaning that patients who would have received the treatment that is optimal for them would have had a post-treatment PHQ-9 score that is two points lower than if they had received the treatment that is suboptimal for them. For 29% of the sample, the PAI was five or greater, which means that a substantial difference between the two treatments was predicted. The use of the PAI approach for clinical practice must be further confirmed in prospective research; the current study supports the identification of specific interventions favorable for specific patients.
Identifiants
pubmed: 32054084
pii: jcm9020490
doi: 10.3390/jcm9020490
pmc: PMC7073663
pii:
doi:
Types de publication
Journal Article
Langues
eng
Déclaration de conflit d'intérêts
The authors declare no conflict of interest.
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