Reading Time: 3 minutes

Today, we will look at the cumulative evidence regarding Feedback Informed Treatment (FIT). 

Research: Latest Meta Analysis. Can you believe it that there’s now nine meta-analyses being done on examining studies on the effects of feedback tools? The latest MA is published by ​Kim de Jong and colleagues​ in Netherlands. 

They looked at 58 studies (over 21,000 clients) in total, using a broader inclusion criteria and more sophisticated statistical analysis (multi-level modeling). 

Key Graf:

– Small positive effect on symptom reduction.

– Reduction in dropout rates.

Effects of feedback in full group (On-Track and Not-On-Track cases combined). Note: This forest plot is a graphical representation of the average effect sizes per study. Data was analyzed in a multilevel model, in which effect sizes per outcome
Effect of feedback in Not-On-Track subgroup i.e., Cases at risk for negative outcomes. Note. This forest plot is a graphical representation of the average effect sizes per study. Data was analysed in a multilevel model, in which effect sizes per outcome measure were nested within studies. The Random Effects (RE) model summary represents the outcome of this model. A random effects model in this study refers to a statistical approach used in meta-analysis to account for different sources of variability in effect sizes observed across multiple studies

Secondary Findings: 

  • Over Time: The study found that the effect of feedback on symptom reduction slightly reduced over time, with an average 0.02 lower effect size per year.
  • Deterioration: There was no significant effect of feedback on the rate of deteriorated cases. On average, 5.4% of patients in control conditions deteriorated, compared to 4.6% in feedback conditions
  • No. of Sessions: The study found no significant overall effect of feedback on the number of sessions (d = -0.04), nor were there significant effects for “On Track” (OT) or Not-On-Track (NOT) cases specifically
  • Feedback Systems: Studies using the Outcome Rating Scale (ORS) and Session Rating Scale (SRS) i.e., PCOMS system had significantly larger effects compared to the Outcome Questionaire (OQ)-45. The researchers noted that ORS is more sensitive to change and might overestimate effect sizes of feedback. However, the OQ System seemed more effective in NOT cases, especially with Clinical Support Tools (CSTs). 
  • Therapist Training (for deteriorated cases): Studies where therapists received training in the feedback systemshowed larger effects in reducing deteriorated cases compared to studies without training.
  • Country: Interestingly, studies conducted in the US showed significantly larger effects of feedback for symptom reduction and dropout rates compared to studies conducted in other countries

In short, measurement by itself isn’t a silver bullet. It is what we do with the feedback to feed-forward into the treatment process that really counts.

Next week, we will look at some of the critique and issues with implementation of FIT. 

Related Articles

When The Pill Model Doesn’t Work

What’s right may not be right for you, and the trappings of misreading research. 

Why We Need Adjustable Seats

Fit the individual and not the average.

1 Response

  1. July 22, 2025

    […] the previous post, we looked at the latest meta-analysis on the effects of feedback […]

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.