Predicting treatment failure in regular care Internet-Delivered Cognitive Behavior Therapy for depression and anxiety using only weekly symptom measures.


Journal

Journal of consulting and clinical psychology
ISSN: 1939-2117
Titre abrégé: J Consult Clin Psychol
Pays: United States
ID NLM: 0136553

Informations de publication

Date de publication:
Apr 2020
Historique:
pubmed: 13 12 2019
medline: 17 9 2020
entrez: 13 12 2019
Statut: ppublish

Résumé

Therapist guided Internet-Delivered Cognitive Behavior Therapy (ICBT) is effective, but as in traditional CBT, not all patients improve, and clinicians generally fail to identify them early enough. We predict treatment failure in 12-week regular care ICBT for Depression, Panic disorder and Social anxiety disorder, using only patients' weekly symptom ratings to identify when the accuracy of predictions exceed 2 benchmarks: (a) chance, and (b) empirically derived clinician preferences for actionable predictions. Screening, pretreatment and weekly symptom ratings from 4310 regular care ICBT-patients from the Internet Psychiatry Clinic in Stockholm, Sweden was analyzed in a series of regression models each adding 1 more week of data. Final score was predicted in a holdout test sample, which was then categorized into Success or Failure (failure defined as the absence of both remitter and responder status). Classification analyses with Balanced Accuracy and 95% Confidence intervals was then compared to predefined benchmarks. Benchmark 1 (better than chance) was reached 1 week into all treatments. Social anxiety disorder reached Benchmark 2 (> 65%) at week 5, whereas Depression and Panic Disorder reached it at week 6. For depression, social anxiety and panic disorder, prediction with only patient-rated symptom scores can detect treatment failure 6 weeks into ICBT, with enough accuracy for a clinician to take action. Early identification of failing treatment attempts may be a viable way to increase the overall success rate of existing psychological treatments by providing extra clinical resources to at-risk patients, within a so-called Adaptive Treatment Strategy. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Identifiants

pubmed: 31829635
pii: 2019-76267-001
doi: 10.1037/ccp0000462
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

311-321

Subventions

Organisme : Stiftelsen Professor Bror Gadelius Minnesfond
Organisme : L.J. Boëthius Stiftelse
Organisme : Vetenskapsrådet
Organisme : Familjen Erling-Perssons Stiftelse
Organisme : ALF Högre Klinisk Forskare

Auteurs

Erik Forsell (E)

Centre for Psychiatry Research.

Nils Isacsson (N)

Centre for Psychiatry Research.

Kerstin Blom (K)

Centre for Psychiatry Research.

Susanna Jernelöv (S)

Centre for Psychiatry Research.

Fehmi Ben Abdesslem (F)

RISE Research Institutes of Sweden.

Nils Lindefors (N)

Centre for Psychiatry Research.

Magnus Boman (M)

Department of Software and Computer Systems.

Viktor Kaldo (V)

Centre for Psychiatry Research.

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Classifications MeSH