Evidence map›Paper›PMID 32482344›Full record

SynthesisNursing outlook

An integrated model of multimorbidity and symptom science.

Toni Tripp-Reimer, Janet K Williams, Sue E Gardner, Barbara Rakel, Keela Herr, Ann Marie McCarthy, Linda Liu Hand, Stephanie Gilbertson-White, Catherine Cherwin

Abstract readSystematic Review
In one paragraph

Synthesis in Nursing outlook. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

9 authors.

Toni Tripp-ReimerCollege of Nursing, The University of Iowa, Iowa City, IA.
Janet K WilliamsCollege of Nursing, The University of Iowa, Iowa City, IA. Electronic address: janet-williams@uiowa.edu.
Sue E GardnerCollege of Nursing, The University of Iowa, Iowa City, IA.
Barbara RakelCollege of Nursing, The University of Iowa, Iowa City, IA.
Keela HerrCollege of Nursing, The University of Iowa, Iowa City, IA.
Ann Marie McCarthyCollege of Nursing, The University of Iowa, Iowa City, IA.
Linda Liu HandCollege of Nursing, The University of Iowa, Iowa City, IA.
Stephanie Gilbertson-WhiteCollege of Nursing, The University of Iowa, Iowa City, IA.
Catherine CherwinCollege of Nursing, The University of Iowa, Iowa City, IA.

Funding

Exploratory Center of Excellence for Advancing Multimorbidity Science (CAMS)P20NR018081 · NINR · UNIVERSITY OF IOWA · PI WILLIAMS, JANET K. · 2018 to 2022
$2.2M
NINR NIH HHS P20 NR018081
6 · The paper itself

Abstract

backgroundPrevalence and complexity of persons with multiple chronic conditions (MCC), also known as multimorbidity, are shifting clinical practice from a single disease focus to one considering MCC and symptoms. Although symptoms are intricately bound to concepts inherent in MCC science, symptoms are largely ignored in multimorbidity research and literature. PURPOSE: Introduce an Integrated Model of Multimorbidity and Symptom Science.

methodsCritical integrative review and synthesis process.

findingsThe model comprises three primary domains: 1. Contributing/ Risk Factors; 2. Symptom/Disease/Treatment Interactions; and 3. Patient Outcomes. DISCUSSION: The model highlights the multilevel nature of contributing factors and the recursive interactions among multiple etiologies, conditions, symptoms, therapies, and outcomes.

Indexed as

Models, StatisticalMultimorbidityChronic DiseaseHumansNursing CarePrevalenceRisk FactorsSymptom AssessmentConceptual modelMultimorbidityMultiple chronic conditionsNursingPrecision healthSymptoms

Identifiers

PMID32482344
PMCPMC7483649

What OpenQuestion holds

Textmetadata
LicenceTDM
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.