Skip to main content

Investigation of physical activity, sleep, and mental health recovery in treatment resistant depression (TRD) patients receiving repetitive transcranial magnetic stimulation (rTMS) treatment

Griffiths, Chris, da Silva, Ksenija Maravic, Leathlean, Chloe, Jianga, Harmony, Ang, Chee Siang, Searle, Ryan (2022) Investigation of physical activity, sleep, and mental health recovery in treatment resistant depression (TRD) patients receiving repetitive transcranial magnetic stimulation (rTMS) treatment. Journal of Affective Disorders Reports, 8 . Article Number 100337. ISSN 2666-9153. (doi:10.1016/j.jadr.2022.100337) (KAR id:93717)

PDF Publisher pdf
Language: English


Download (824kB) Preview
[thumbnail of 1-s2.0-S2666915322000300-main.pdf]
Preview
This file may not be suitable for users of assistive technology.
Request an accessible format
PDF Author's Accepted Manuscript
Language: English

Restricted to Repository staff only
Contact us about this Publication
[thumbnail of JADR-D-21-00251_R1 resubmission.pdf]
Official URL:
https://doi.org/10.1016/j.jadr.2022.100337

Abstract

Background : Repetitive transcranial magnetic stimulation (rTMS) is effective in treating depression; however, the effect on physical activity, sleep and recovery is unclear. This study investigated rTMS effect on physical activity and sleep through providing patients with a Fitbit and software apps; and reports the impact of rTMS on depression, anxiety and mental health recovery.

Methods : Study design was a pre and post data collection without a control, with twenty-four participants with treatment-resistant depression (TRD). Measures used were Fitbit activity and sleep data, and patient-rated Recovering Quality of Life (ReQoL-20), Patient Health Questionnaire (PHQ-9) and Generalised Anxiety Disorder (GAD-7).

Results : Response and remission rates were, respectively: 34.8% and 39% for PHQ-9; 34.8% and 47.8% for GAD-7. ReQoL-20 response and reliable improvement were 29.4% and 53%. PHQ-9, GAD-7 and ReQol-20 scores significantly improved, with large effect sizes. Analysis of Fitbit activity and sleep data yielded non-significant results. The Fitbit data machine learning model classified two levels of depression to 82% accuracy.

Limitations : rTMS treatment was open-label and adjunct to existing antidepressant medication. No control group. Female patients were overrepresented.

Conclusions : Improvements on the ReQoL-20 and aspects of sleep and activity indicate the positive impact of rTMS on the individual’s real world functioning and quality of life. A wearable activity tracker can provide feedback to patients and clinicians on sleep, physical activity and depression levels. Further research could be undertaken through a sufficiently powered RCT comparing rTMS versus rTMS with use of a Fitbit, its software applications, and sleep and physical activity advice.

Item Type: Article
DOI/Identification number: 10.1016/j.jadr.2022.100337
Uncontrolled keywords: Depression, Fitbit, exercise, activity, sleep, recovery, rTMS
Subjects: Q Science > Q Science (General) > Q335 Artificial intelligence
R Medicine > RC Internal medicine > RC321 Neuroscience. Biological psychiatry. Neuropsychiatry
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Jim Ang
Date Deposited: 24 Mar 2022 15:50 UTC
Last Modified: 25 Mar 2022 09:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/93717 (The current URI for this page, for reference purposes)
Ang, Chee Siang: https://orcid.org/0000-0002-1109-9689
  • Depositors only (login required):

Downloads

Downloads per month over past year