Evidence map›Paper›PMID 40008009›Full record

ArticleInnovation in aging2025

Latent Class Analysis Identifies Four Distinct Patient Deprescribing Typologies Among Older Adults in Four Countries.

Kristie Rebecca Weir, Vincent D Marshall, Sarah E Vordenberg

Registry-linked trialAbstract read
In one paragraph

Article in Innovation in aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04676282 (Psychological and Clinical Factors That Predict Intent to Deprescribe Medications Among Older Adults), which is not on this map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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.

NCT04676282 completednot on this map

Psychological and Clinical Factors That Predict Intent to Deprescribe Medications Among Older Adults

TypeobservationalSponsorUniversity of MichiganRan2020 to 2021Enrolled10,184ConditionsPolypharmacy, AgingArmsHypothetical Scenario
3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
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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

3 authors.

Kristie Rebecca WeirSydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
Vincent D MarshallUniversity of Michigan College of Pharmacy, Ann Arbor, Michigan, USA.
Sarah E VordenbergUniversity of Michigan College of Pharmacy, Ann Arbor, Michigan, USA.ORCID https://orcid.org/0000-0002-9828-9759

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: Polypharmacy, the concurrent use of multiple medicines, is a growing concern among older adults and those with chronic conditions. Deprescribing through dose reduction or discontinuing selected medicines is a strategy for reducing medicine-related harm. The Patient Deprescribing Typology was developed using qualitative methods to describe the varying factors that are important to older adults when they consider deprescribing. The objective of this study was to use quantitative methods to define distinct classes of older adults via the Patient Deprescribing Typology. Research Design and Methods: This study used a cross-sectional experimental design in which data was collected via an online survey from participants 65 years and older in Australia, the Netherlands, the United Kingdom, and the United States. A latent class analysis was performed using the 4-item Patient Deprescribing Typology that collected data about the beliefs about the importance of medicines, how older adults learn about medicines, medicine decision-making preferences, and attitudes towards stopping medicines. Results: Older adults ( Discussion and Implications: Older adults report diverse perspectives about deprescribing, emphasizing the need for tailored communication strategies in clinical settings. Additional research is needed to examine older adults' preferences in real-world contexts to refine and improve deprescribing interventions. Clinical Trial Registration: NCT04676282.

Indexed as

AttitudesDeprescriptionHealth care communicationMedicinePatient preferences

Identifiers

PMID40008009
PMCPMC11851471

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Registered trials

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.