Evidence map›Paper›PMID 37106334›Full record

ArticleBMC geriatrics2023

Differences in the longitudinal change of behaviours related to dementia in long-term care: a growth mixture modelling approach.

Annie Robitaille, Linda Garcia, Graciela Muniz Terrera

Abstract read
In one paragraph

Article in BMC geriatrics, 2023. 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. 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

3 authors.

Annie RobitailleFaculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada. arobitai@uottawa.ca.
Linda GarciaFaculty of Health Sciences, University of Ottawa, Ottawa, ON, Canada.
Graciela Muniz TerreraOhio University Heritage College of Osteopathic Medicine, Ohio University, Athens, OH, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is still a need for more information about the different trajectories of responsive behaviours that people living with dementia present in long-term care homes (LTC).

objectiveThis study identified subgroups of individuals with similar trajectories of responsive behaviours related to dementia in LTC and evaluated the role of demographic variables, depressive symptomatology, social engagement, cognitive functioning, and activities of daily living (ADL) on class membership.

methodsGrowth mixture models were run using data from the Continuing Care Reporting System.

resultsResults suggest that change in responsive behaviours is best represented by seven classes of trajectories. The largest class was composed of individuals who presented the lowest frequency of behaviours upon entry in LTC that increased at a slow linear rate. The other classes were composed of individuals who presented different frequencies of behaviours upon entry in LTC and varying rates of change (e.g., individuals who presented a low frequency of behaviours upon entry in LTC that increased at a linear rate followed by a decrease in the later months, individuals who presented a high frequency of responsive behaviours upon entry in LTC and that remained stable). Cognitive functioning, social engagement, depressive symptomatology, and ADL were markers of class membership.

conclusionsThese findings can help identify individuals at increased risk of presenting a high frequency of responsive behaviours and highlight interventions that could decrease behaviours in LTC.

Indexed as

DementiaLong-Term CareActivities of Daily LivingCognitionHumansDementiaGrowth mixture modelLongitudinal dataLong-term careResponsive behaviours

Identifiers

PMID37106334
PMCPMC10141941

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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.