Evidence map›Paper›PMID 39210277›Full record

ArticleBMC geriatrics2024

Predicting informal dementia caregivers' desire to institutionalize through mining data from an eHealth platform.

Soraia Teles, João Viana, Alberto Freitas, Óscar Ribeiro, Sara Alves, Ana Ferreira, Constança Paúl

Abstract read
In one paragraph

Article in BMC geriatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Experience of Conjugality Among Older People in Long-Term Care Facilities: A Scoping Review.Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2026
    Article
  2. 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.

Soraia TelesDepartment of Behavioral Sciences, School of Medicine and Biomedical Sciences, University of Porto (ICBAS-UP), Rua de Jorge Viterbo Ferreira, 228, Porto, 4050-313, Portugal. stsousa@icbas.up.pt.
João VianaCenter for Health Technology and Services Research at Health Research Network (CINTESIS@RISE), Rua Dr. Plácido da Costa, Porto, 4200-450, Portugal.
Alberto FreitasCenter for Health Technology and Services Research at Health Research Network (CINTESIS@RISE), Rua Dr. Plácido da Costa, Porto, 4200-450, Portugal.
Óscar RibeiroCenter for Health Technology and Services Research at Health Research Network (CINTESIS@RISE), Rua Dr. Plácido da Costa, Porto, 4200-450, Portugal.
Sara AlvesCenter for Health Technology and Services Research at Health Research Network (CINTESIS@RISE), Rua Dr. Plácido da Costa, Porto, 4200-450, Portugal.
Ana FerreiraCenter for Health Technology and Services Research at Health Research Network (CINTESIS@RISE), Rua Dr. Plácido da Costa, Porto, 4200-450, Portugal.
Constança PaúlDepartment of Behavioral Sciences, School of Medicine and Biomedical Sciences, University of Porto (ICBAS-UP), Rua de Jorge Viterbo Ferreira, 228, Porto, 4050-313, Portugal.

Funding

Fundação para a Ciência e a Tecnologia 2022.07587.PTDC; DOI: 10.54499/2022.07587.PTDC
6 · The paper itself

Abstract

backgroundDementia is a leading factor in the institutionalization of older adults. Informal caregivers' desire to institutionalize (DI) their care recipient with dementia (PwD) is a primary predictor of institutionalization. This study aims to develop a prediction model for caregivers' DI by mining data from an eHealth platform in a high-prevalence dementia country.

methodsCross-sectional data were collected from caregivers registering on isupport-portugal.pt. One hundred and four caregivers completed the Desire to Institutionalize Scale (DIS) and were grouped into DI (DIS score ≥ 1) and no DI (DIS score = 0). Participants completed a comprehensive set of sociodemographic, clinical, and psychosocial measures, pertaining to the caregiver and the PwD, which were accounted as model predictors. The selected model was a classification tree, enabling the visualization of rules for predictions.

resultsCaregivers, mostly female (82.5%), offspring of the PwD (70.2), employed (65.4%), and highly educated (M 15 years of schooling), provided intensive care (Mdn 24 h. week) over a median course of 2.8 years. Two-thirds (66.3%) endorsed at least one item on the DIS (DI group). The model, with caregivers' perceived stress as the root of the classification tree (split at 28.5 points on the Zarit Burden Interview) and including the ages of caregivers and PwD (split at 46 and 88 years, respectively), as well as cohabitation, employed five rules to predict DI. Caregivers scoring 28.5 and above on burden and caring for PwD under 88 are more prone to DI than those caring for older PwD (rules 1-2), suggesting the influence of expectations on caregiving duration. The model demonstrated high accuracy (0.83, 95%CI 0.75, 0.89), sensitivity (0.88, 95%CI 0.81, 0.95), and good specificity (0.71, 95%CI 0.56, 0.86).

conclusionsThis study distilled a comprehensive range of modifiable and non-modifiable variables into a simplified, interpretable, and accurate model, particularly useful at identifying caregivers with actual DI. Considering the nature of variables within the prediction rules, this model holds promise for application to other existing datasets and as a proxy for actual institutionalization. Predicting the institutional placement of PwD is crucial for intervening on modifiable factors as caregiver burden, and for care planning and financing.

Indexed as

CaregiversData MiningDementiaInstitutionalizationTelemedicineAgedAged, 80 and overCross-Sectional StudiesFemaleHumansMaleMiddle AgedPortugalClassification treeDementiaDesire to institutionalizeeHealthInformal caregiversPlatform data

Identifiers

PMID39210277
PMCPMC11363529

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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.