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Prevalence of depression in amyotrophic lateral sclerosis/motor neuron disease: multi-attribute ascertainment and trajectories over 30 months

Lookup NU author(s): Dr Timothy Williams


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© 2022 World Federation of Neurology on behalf of the Research Group on Motor Neuron Diseases.Objective: Evidence is equivocal about the prevalence of depression in amyotrophic lateral sclerosis (ALS). This study uses a multi-attribute ascertainment of the prevalence of depression and examines this prevalence over time. Methods: Patients with ALS were recruited into the Trajectories of Outcome in Neurological Conditions (TONiC-ALS) study. Caseness was identified by the Modified-Hospital Anxiety and Depression Scale (M-HADS). In addition, participants provided data on co-morbidities and medication use. A combination of the three was used to derive the estimate for the prevalence of depression, treated or untreated. Longitudinal data were analyzed by trajectory analysis of interval level M-HADS-Depression data. Results: Among 1120 participants, the mean age was 65.0 years (SD 10.7), 60.4% male, and the median duration since diagnosis was 9 months (IQR 4–24). Caseness of probable depression at baseline, defined by M-HADS-Depression, was 6.45% (95%CI: 5.1–8.0). Taken together with antidepressant medication and co-morbidity data, the prevalence of depression was 23.1% (95%CI: 20.7–25.6). Of those with depression, 17.8% were untreated. Trajectory analysis identified three groups, one of which contained the most cases; the level of depression for each group remained almost constant over time. Conclusion: Depression affects almost a quarter of those with ALS, largely confined to a single trajectory group. Prevalence estimates based on screening for current depressive symptoms substantially under-estimate the population experiencing depression. Future prevalence studies should differentiate data based on current symptoms from those including treated patients. Both have their place in assessing depression and the response by the health care system, including medication, depending upon the hypothesis under test.

Publication metadata

Author(s): Young CA, Ealing J, McDermott CJ, Williams TL, Al-Chalabi A, Majeed T, Talbot K, Harrower T, Faull C, Malaspina A, Annadale J, Mills RJ, Tennant A

Publication type: Article

Publication status: Published

Journal: Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration

Year: 2023

Volume: 24

Issue: 1-2

Pages: 82-90

Online publication date: 06/09/2022

Acceptance date: 28/06/2022

ISSN (print): 2167-8421

ISSN (electronic): 2167-9223

Publisher: Taylor and Francis Ltd.


DOI: 10.1080/21678421.2022.2096410

PubMed id: 36066075


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