Identifying patients with therapy-resistant depression by using factor analysis

Research output: Contribution to journalJournal articleResearchpeer-review

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.
Original languageEnglish
JournalPharmacopsychiatry
Volume43
Issue number7
Pages (from-to)252-6
Number of pages5
ISSN0176-3679
DOIs
Publication statusPublished - 1 Nov 2010

    Research areas

  • Antidepressive Agents, Clinical Trials as Topic, Depressive Disorder, Major, Drug Resistance, Factor Analysis, Statistical, Female, Humans, Male, Placebos, Principal Component Analysis, Psychiatric Status Rating Scales, Transcranial Magnetic Stimulation, Treatment Failure, Treatment Outcome

ID: 33265041