Evidence map›Paper›PMID 35608072›Full record

ArticleHealth expectations : an international journal of public participation in health care and health policy2022

Perspectives of people living with Parkinson's disease on personalized prediction models.

Lieneke van den Heuvel, Marjan Knippenberg, Bart Post, Marjan J Meinders, Bastiaan R Bloem, Anne M Stiggelbout

Open access · goldAbstract read
In one paragraph

Article in Health expectations : an international journal of public participation in health care and health policy, 2022. 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
0.4field-weighted citation impact, top 39% of its field
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, 3 citations in OpenAlex.

  1. Article
  2. Perspectives of people living with Parkinson's disease on personalized prediction models.Health expectations : an international journal of public participation in health care and health policy · 2022
    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

6 authors at 2 institutions in 1 country.

Lieneke van den HeuvelDepartment of Neurology, Centre of Expertise for Parkinson and Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands.ORCID 0000-0001-5798-6251
Marjan KnippenbergScientific Centre for Quality of Healthcare, Radboud Institute for Health Sciences, Radboud University Medical Centre, Nijmegen, The Netherlands.ORCID 0000-0001-9707-7458
Bart PostDepartment of Neurology, Centre of Expertise for Parkinson and Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands.ORCID 0000-0002-7271-864X
Marjan J MeindersScientific Centre for Quality of Healthcare, Centre of Expertise for Parkinson and Movement Disorders, Radboud Institute for Health Sciences, Radboud University Medical Centre, Nijmegen, The Netherlands.ORCID 0000-0001-6491-7035
Bastiaan R BloemDepartment of Neurology, Centre of Expertise for Parkinson and Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands.ORCID 0000-0002-6371-3337
Anne M StiggelboutDepartment of Biomedical Data Sciences, Medical Decision Making, Leiden University Medical Centre, Leiden, The Netherlands.ORCID 0000-0002-6293-4509
Radboud University Nijmegen · NLLeiden University Medical Center · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere is a great need for the development of personalized prediction models (PPMs) that can predict the rate of disease progression for persons with Parkinson's disease (PD), based on their individual characteristics. In this study, we aimed to clarify the perspective of persons diagnosed with PD on the value of such hypothetical PPMs.

methodsWe organized four focus group discussions, each including five persons with PD who were diagnosed within the last 5 years. The sessions focused on what they think of receiving a personalized prediction; what outcomes are important to them; if and how the possibility of influencing the prognosis would change the way they think of personalized predictions; how they deal with the uncertainty from a PPM; and what barriers and facilitators they expect for using a PPM.

resultsThe wish of persons with PD for receiving personalized prognostic information was highly heterogenous, for various reasons. Most persons with PD would like to receive more personalized prognostic information, mainly to better prepare themselves and their loved ones for the future. The prediction provided should be as personalized as possible, and there should be adequate supervision and coaching by a professional when providing the information. They were particularly interested in receiving prognostic information when their interventions would be available that could subsequently influence the identified prognostic factor and thereby affect the disease course beneficially.

conclusionMost persons with PD in this study want more insight into their own future by means of prediction models, provided that this is explained and supervized properly by professionals. PATIENT OR PUBLIC CONTRIBUTION: Two patient-researchers were involved in the study design, conduct of the study, interpretation of the data and in preparation of the manuscript.

Indexed as

Parkinson DiseaseFocus GroupsHumansPrecision MedicinePrognosisResearch DesignRisk AssessmentParkinson's diseasepatients' perspectivepersonalized prediction model

Identifiers

PMID35608072
PMCPMC9327833
OpenAlexW4282924799

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.