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Updated: Jun 9, 2026

Individualized rTMS Treatment for Depression using an fMRI-Based Targeting Method
Published on: August 2, 2021
Identifying patients with therapy-resistant depression by using factor analysis
K Andreasson1, V Liest, M Lunde
1Psychiatric Research Unit, Frederiksborg General Hospital, Hillerød, Denmark.
Introduction:
Attempts to identify the factor structure in patients with treatment-resistant depression have been very limited.
Methods:
Principal component analysis was performed using the baseline datasets from 3 add-on studies [2 with repetitive transcranial magnetic stimulation and one with transcranial pulsed electromagnetic fields (T-PEMF)], in which the relative effect as percentage of improvement during the treatment period was analysed.
Results:
We identified 2 major factors, the first of which was a general factor. The second was a dual factor consisting of a depression subscale comprising the negatively loaded items (covering the pure depression items) and a treatment resistant subscale comprising the positively loaded items (covering lassitude, concentration difficulties and sleep problems). These 2 dual subscales were used as outcome measures. Improvement on the treatment resistant subscale was 40% in the active treatment group compared to 17-30% improvement in the sham treatments.
Discussion:
It is possible to describe patients with therapy-resistant depression by a factor structure. Both rTMS and T-PEMF had a clinical effect on the factor-derived scales when compared to sham treatment.
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