# Effects of electroconvulsive therapy on suicide in geriatrics patients with major depressive disorder: a nationwide cohort study using propensity score matching and instrumental variable analysis

> **NIH NIH R21** · YALE UNIVERSITY · 2020 · $125,625

## Abstract

Project Abstract
The proposed study aims to determine the effect of ECT on completed suicides in geriatric patients with major
depressive disorder (MDD). Data will be drawn from both the Medicare datasets and the National Death Index.
To examine the effect of ECT on suicide, we will use an instrumental variables analysis, which accounts for
unmeasured confounders, applied to propensity score-matched data. Prior to applying the propensity score
model, patients will be individually matched on age, gender, number of antidepressant trials and medically
treated suicide attempts in the preceding year. The instrumental variable will be the proportion of patients with
MDD treated with ECT in each hospital in the prior calendar year; this instrument has been used successfully
in a previous study of ECT and 30-day readmission risk. The primary outcome of the comparison will be
completed suicide; secondary outcomes will include all-cause mortality.
 Suicide is a major public health crisis and, despite renewed efforts by public health leaders, the suicide
rate has been increasing in the last 15 years. Most suicide victims suffer from treatable psychiatric disorders,
most commonly a mood disorder such as MDD. ECT is the most effective treatment for MDD and professional
guidelines recommend ECT as a treatment for severely ill patients with mood disorders who are at high risk of
suicide. However, there is a critical gap in our understanding of the relationship between ECT and suicide;
there has not been a convincing and consistent link between and reduced risk of completed suicide. The
proposed study aims to fill this gap. Our study focuses on an enriched sample of geriatric patients, who
experience particular benefit from ECT and are more likely than younger patients to receive the treatment.
Additionally, this age group is historically at high risk for suicide.
 The proposed study is of central relevance to the NIMH mission of reducing suicide rates. Despite ECT
being the most effective and definitive therapy for severe depression, it has been dogged by stigma for
decades. However, the last several years have seen a surge in high-quality ECT research published in
prominent journals reiterating the effectiveness of ECT, developing algorithms for predicting clinical outcomes,
improving longer-term outcomes, showing its potential benefits on population health outcomes, and suggesting
it is most cost-effective when used after a 2nd failed antidepressant trial. Given this resurgence of ECT
research, the proposed study is both timely and of critical importance to reducing suicide rates. If, as
hypothesized, ECT is shown to be associated with reduced rates of ECT, future research could aim to increase
the dissemination of this critical treatment and study barriers to treatment access. Furthermore, the lack of a
consistent link between ECT and reduced suicide rates is often used by anti-psychiatry/anti-ECT advocates to
protest the use of the treatment. If ECT can con...

## Key facts

- **NIH application ID:** 9886271
- **Project number:** 5R21MH117438-02
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** SAMUEL WILKINSON
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $125,625
- **Award type:** 5
- **Project period:** 2019-03-05 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9886271

## Citation

> US National Institutes of Health, RePORTER application 9886271, Effects of electroconvulsive therapy on suicide in geriatrics patients with major depressive disorder: a nationwide cohort study using propensity score matching and instrumental variable analysis (5R21MH117438-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9886271. Licensed CC0.

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