A Probabilistic and Individualized Approach for Predicting Treatment Gains: An Extension and Application to Anxiety Disordered Youth

Rinad S. Beidas*, Oliver Lindhiem, Douglas M. Brodman, Anna Swan, Matthew Carper, Colleen Cummings, Philip C. Kendall, Anne Marie Albano, Moira Rynn, John Piacentini, James McCracken, Scott N. Compton, John March, John Walkup, Golda Ginsburg, Courtney P. Keeton, Boris Birmaher, Dara Sakolsky, Joel Sherrill

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

The objective of this study was to extend the probability of treatment benefit method by adding treatment condition as a stratifying variable, and illustrate this extension of the methodology using the Child and Adolescent Anxiety Multimodal Study data. The probability of treatment benefit method produces a simple and practical way to predict individualized treatment benefit based on pretreatment patient characteristics. Two pretreatment patient characteristics were selected in the production of the probability of treatment benefit charts: baseline anxiety severity, measured by the Pediatric Anxiety Rating Scale, and treatment condition (cognitive-behavioral therapy, sertraline, their combination, and placebo). We produced two charts as exemplars which provide individualized and probabilistic information for treatment response and outcome to treatments for child anxiety. We discuss the implications of the use of the probability of treatment benefit method, particularly with regard to patient-centered outcomes and individualized decision-making in psychology and psychiatry.

Original languageEnglish (US)
Pages (from-to)126-136
Number of pages11
JournalBehavior Therapy
Volume45
Issue number1
DOIs
StatePublished - 2014

Funding

Keywords

  • Child/adolescent anxiety
  • Evidence-based treatment
  • Individualized treatment benefit
  • Patient-centered decision-making
  • Treatment response and outcome

ASJC Scopus subject areas

  • Clinical Psychology

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