Sine of the times: Can sinusoidal waves model changes in the therapeutic alliance over time?

Jonathan G. Shalom, Maya Korem, Asher Y. Strauss, Jonathan D. Huppert, Gerhard Andersson, Idan M. Aderka

Research output: Contribution to journalArticlepeer-review

Abstract

The present study examined the association between the therapeutic alliance and social anxiety symptoms during internet-delivered cognitive behavior therapy (ICBT) for social anxiety disorder (SAD). We examined 162 individuals diagnosed with SAD who underwent therapist-assisted ICBT and completed measures of the therapeutic alliance weekly during a randomized controlled trial. We used a novel modeling strategy and modeled changes in the therapeutic alliance over time using sinusoidal models. We found that a model that incorporated both a linear component and a sinusoidal component (r2 = 0.72), explained significantly more variance than models using only linear (r2 = 0.42) or only sinusoidal (r2 = 0.41) components. We also found that higher average levels of the alliance as well as greater increases in the therapeutic alliance during treatment were associated with greater reductions in social anxiety during treatment. Finally, we found that greater fluctuations around the slope of alliance were associated with greater reductions in social anxiety during treatment (above and beyond average alliance and increases in alliance). Considering fluctuations around a linear slope may be a useful model for the ups and downs experienced in the therapeutic alliance over the course of therapy. Fluctuations in alliance may not be a sign of negative processes, but could potentially indicate a healthy ebb and flow of the alliance that is predictive of better outcomes.

Original languageEnglish
Article number100845
JournalInternet Interventions
Volume41
DOIs
StatePublished - Sep 2025

Keywords

  • Internet-delivered CBT
  • Sinusoidal models
  • Social anxiety
  • Social anxiety disorder
  • Therapeutic alliance

All Science Journal Classification (ASJC) codes

  • Health Informatics

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