Evidence map›Paper›PMID 42089534›Full record

ArticleJournal of the American Geriatrics Society2026

Antidepressant Use Among US Nursing Home Residents With Dementia.

Shiwei Liang, Kate L Lapane, Brian R Ott, Jennifer Tjia, Jonggyu Baek, Yiyang Yuan, Matthew Alcusky

Abstract read
In one paragraph

Article in Journal of the American Geriatrics Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Antidepressant Use Among US Nursing Home Residents With Dementia.Journal of the American Geriatrics Society · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Shiwei LiangDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA.ORCID 0000-0001-7845-3534
Kate L LapaneDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA.ORCID 0000-0001-9957-7747
Brian R OttDepartment of Neurology, Brown University Warren Alpert Medical School, Providence, Rhode Island, USA.ORCID 0000-0002-4899-7116
Jennifer TjiaDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA.ORCID 0000-0003-4541-0460
Jonggyu BaekDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA.
Yiyang YuanDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA.ORCID 0000-0002-8322-5648
Matthew AlcuskyDepartment of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Worcester, Massachusetts, USA.

Funding

Antidementia medication use, safety, and effectiveness among nursing home residents with Alzheimer's diseaseR01AG068450 · NIA · UNIV OF MASSACHUSETTS MED SCH WORCESTER · PI ALCUSKY, MATTHEW · 2020 to 2022
$2.3M
NIA NIH HHS 5R01AG068450-03NIA NIH HHS R01 AG068450
6 · The paper itself

Abstract

backgroundIn 2024, 6.9 million Americans lived with Alzheimer's disease and related dementias (ADRD), with nursing homes serving as a major site of care. Antidepressants are the most prescribed psychotropic medications among nursing home residents with ADRD, yet detailed information on prescribing patterns, potential indications, and associated resident and facility characteristics remain limited.

methodsUsing 2018 minimum data set 3.0 assessments linked to Medicare claims, we conducted a cross-sectional study of long-stay nursing home residents aged ≥ 65 years with ADRD who were continuously enrolled in Medicare fee-for-service for 120 days before their annual assessment. We described usage by drug class and type and compared characteristics of users versus non-users overall and by potential indications: depression, anxiety, pain, and insomnia.

resultsAmong 232,543 residents with ADRD, 51.6% used antidepressants. Fewer than 5% had moderate or severe depressive symptoms (PHQ-9 ≥ 10). Use was highest among residents with depression or anxiety (69.5%), pain (61.9%), and insomnia (60.0%). Among those without these conditions, 14.1% were prescribed antidepressants. SSRIs were the most prescribed class (60.7%) overall. Citalopram, mirtazapine, sertraline, and trazodone were the most common medications. Residents with any current level of depression severity were more likely to use antidepressants compared to those without symptoms, whereas all levels of cognitive impairment were associated with lower use compared with cognitively intact residents with ADRD. Polypharmacy was strongly associated with increased use, while diabetes, heart failure, and stroke were associated with reduced use.

conclusionsAntidepressants were frequently prescribed to residents with ADRD despite limited documentation of active depressive symptoms. Limitations in accurately capturing depressive symptoms in nursing home records, including underreporting by residents due to cognitive impairment and reliance on staff observation rather than self-report, may contribute to apparent discordance between symptoms and prescribing. Further research should evaluate treatment appropriateness, deprescribing opportunities, and risk-benefit balance of chronic treatment in this population.

Indexed as

Antidepressive AgentsDementiaDepressionNursing Home ResidentsNursing HomesAgedAged, 80 and overCross-Sectional StudiesFemaleHomes for the AgedHumansMaleMedicareUnited StatesAntidepressive AgentsAlzheimer's diseaseantidepressantsdementianursing homes

Identifiers

PMID42089534
PMCPMC13418650

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.