Evidence map›Paper›PMID 31676300›Full record

ArticleApplied nursing research : ANR2019

The Symptoms Self-Management Center (SSMC): Methods for developing and implementing technology-enhanced self-management interventions for pain and fatigue.

Shannon Phillips, Julie Barroso, Ronald Acierno, Teresa Kelechi

Abstract read
In one paragraph

Article in Applied nursing research : ANR, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Shannon PhillipsMedical University of South Carolina, College of Nursing, 99 Jonathan Lucas St., Charleston, SC 29425, USA. Electronic address: phillipss@musc.edu.
Julie BarrosoMedical University of South Carolina, College of Nursing, 99 Jonathan Lucas St., Charleston, SC 29425, USA. Electronic address: barroso@musc.edu.
Ronald AciernoMcGovern Medical School at the University of Texas Health Science Center at Houston, Department of Psychiatry and Behavioral Sciences, 6431 Fannin St., Houston TX, 77030. Electronic address: ronald.acierno@uth.tmc.edu.
Teresa KelechiMedical University of South Carolina, College of Nursing, 99 Jonathan Lucas St., Charleston, SC 29425, USA. Electronic address: kelechtj@musc.edu.

Funding

Technology Enhanced Self-Management Interventions for Fatigue and Pain: The Symptoms Self Management Center (Pilot Project Core)P20NR016575 · NINR · MEDICAL UNIVERSITY OF SOUTH CAROLINA · PI KELECHI, TERESA J · 2016 to 2020
$2.0M
NINR NIH HHS P20 NR016575
6 · The paper itself

Abstract

The National Institutes of Nursing Research provides funding via the P20 grant mechanism for research infrastructure and resources to develop nurse scientists with expertise in symptom self-management. The Medical University of South Carolina College of Nursing was awarded a P20 grant in 2016 to build the Symptoms Self-Management Center for technology-enhanced interventions to address pain and fatigue in individuals with chronic health conditions. Resources were derived from three key subcores: bioinformatics, mHealth and eHealth consultative services, and community engagement. This paper describes methods for deriving specific resources within each subcore, the application of subcore resources in two pilot studies, and lessons learned during the early phases of our Symptoms Self-Management Center implementation.

Indexed as

AdolescentAdultAgedAged, 80 and overChildChronic DiseaseFatigueFemaleHumansInventionsMaleMiddle AgedPainPilot ProjectsSelf-ManagementTelemedicine

Identifiers

PMID31676300
PMCPMC6959000

What OpenQuestion holds

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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.