Growth curves of common factors in psychotherapy: Multilevel growth modelling and outcome analysis

Clin Psychol Psychother. 2023 Sep-Oct;30(5):1095-1110. doi: 10.1002/cpp.2864. Epub 2023 May 19.


Objective: A large body of literature discusses change mechanisms underlying psychotherapy with an emphasis on common factors. The present study examined how different comprehensive common factors change over the course of therapy and whether this change was associated with clinical outcome at discharge.

Method: Three hundred forty-eight adults (mean age = 32.1, SD = 10.6; 64% female) attended a standardized 14-week day-clinic psychotherapy program. They provided longitudinal data on common factors based on weekly assessments. Additionally, pre- and post-assessment questionnaires on clinical outcome were completed. Using multilevel modelling, we predicted common factors by time (week in therapy). Multiple linear regression models tested the association between changes in common factors and clinical outcome.

Results: The common factor 'Therapeutic Alliance' was best fitted by linear growth models, whereas models for the common factors 'Coping', 'Cognitive Integration' and 'Affective Processing' indicated logarithmic changes over time. 'Coping', that is change in patients' ability to cope with their individual problems, was most closely linked with outcome.

Conclusions: The present study provides evidence for the changeability of common factors over the course of therapy as well as their specific contributions to psychotherapeutic progress.

Keywords: common factors; day-clinic; multilevel modelling; process-outcome research; psychotherapy.

MeSH terms

  • Adult
  • Female
  • Humans
  • Male
  • Patients
  • Psychotherapy*
  • Therapeutic Alliance*
  • Treatment Outcome