Frontiers Friday #33. Feedback Informed Treatment (FIT; Part I)
Frontiers of Psychotherapist Development
Frontiers Friday #33. Feedback Informed Treatment (FIT; Part I)
To a large degree, so much of our frontier in deep learning, deliberate practice etc is underpinned by Feedback Informed Treatment. FIT is a pantheoretical approach to systemically monitor outcomes and engagement levels on a session-by-session basis, AND using that to guide your clinical practice.
Here are five latest resources to check out. A lot to dive in too. So take your time with these.
Research: Science of FIT Implementation
Heidi Brattland, John Morten and colleagues did a good RCT study examining the implementation of FIT into their agency in Norway. They found that the feedback group were more than 2x likely to achieve improvement, compared to the no-feedback group.
This finding was similar to the one that my colleague Sharon Lu and I did in naturalistic outpatient setting in Singapore, 2009 (Click here to see the poster.)
(Watch this short interview my colleague/friend/mentor Scott Miler did with the lead researcher, Heidi Brattland.)
Research: Critique of FIT
Ole Østergård did his doctoral work based on 3 publications examining the effectiveness and moderators of FIT.
In one of their meta-analysis, the researchers found that the "effects" of FIT is small.
Take a look for yourself before moving on to the next recommendation.
Read: Does This Mean That FIT is Not Working?
My colleague Susanne Bargmann wrote a good blogpost addressing some of the implementation issues (e.g., some studies that were included in the meta-analysis had 1-12hrs of training, whereas studies like Brattland and colleagues indicate that proper implementation takes more time than simple learning to administer the measures).
To read this blogpost in English, click here.
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?
Just this year, a new one is being published by Kim de Jong and colleagues. They looked at 58 studies in total, using a broader inclusion criteria and more sophisticated statistical analysis (multi-level modeling)
Here's the key grafs of what they found:
- small positive effect on symptom reduction
- reduction in dropout rates
Once again, measurement by itself shouldn't be seen as a silver bullet. It is what we do with the feedback to feed-forward into the treatment process that really counts.
Words Worth Contemplating:
The quality of your feedback determines the quality of your learning.
Reflection:
Do you use measures in therapy? If so, do you use them as an assessment tool or a conversational tool?
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