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Randomized Controlled Trial
. 2008 Dec;39(4):398-405.
doi: 10.1016/j.beth.2007.12.002. Epub 2008 Apr 30.

Greater expectations: using hierarchical linear modeling to examine expectancy for treatment outcome as a predictor of treatment response

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Randomized Controlled Trial

Greater expectations: using hierarchical linear modeling to examine expectancy for treatment outcome as a predictor of treatment response

Matthew Price et al. Behav Ther. 2008 Dec.

Abstract

A client's expectation that therapy will be beneficial has long been considered an important factor contributing to therapeutic outcomes, but recent empirical work examining this hypothesis has primarily yielded null findings. The present study examined the contribution of expectancies for treatment outcome to actual treatment outcome from the start of therapy through 12-month follow-up in a clinical sample of individuals (n=72) treated for fear of flying with either in vivo exposure or virtual reality exposure therapy. Using a piecewise hierarchical linear model, outcome expectancy predicted treatment gains made during therapy but not during follow-up. Compared to lower levels, higher expectations for treatment outcome yielded stronger rates of symptom reduction from the beginning to the end of treatment on 2 standardized self-report questionnaires on fear of flying. The analytic approach of the current study is one potential reason that findings contrast with prior literature. The advantages of using hierarchical linear modeling to assess interindividual differences in longitudinal data are discussed.

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Figures

FIGURE 1
FIGURE 1
Change trajectories for treatment outcome as measured by the Questionnaire on Attitudes Towards Flying (QAF).
FIGURE 2
FIGURE 2
Change trajectories for treatment outcome as measured by the Fear of Flying Inventory (FFI).

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