Evidence map›Paper›PMID 31687937›Full record

SynthesisJournal of medical Internet research2019

Electronic Health Self-Management Interventions for Patients With Chronic Kidney Disease: Systematic Review of Quantitative and Qualitative Evidence.

Hongxia Shen, Rianne M J J van der Kleij, Paul J M van der Boog, Xinwei Chang, Niels H Chavannes

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 7 pooled it
20.8field-weighted citation impact, top 1% 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

42 citing papers in PubMed, 7 syntheses or guidelines pooled it, 99 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Hongxia ShenDepartment of Public Health and Primary Care, Leiden University Medical Centre, Leiden, Netherlands.ORCID 0000-0002-0601-4708
Rianne M J J van der KleijDepartment of Public Health and Primary Care, Leiden University Medical Centre, Leiden, Netherlands.ORCID 0000-0002-8638-4978
Paul J M van der BoogDepartment of Nephrology, Leiden University Medical Centre, Leiden, Netherlands.ORCID 0000-0002-8178-1413
Xinwei ChangDepartment of Surgery, School of Nutrition and Translational Research in Metabolism, Maastricht University, Maastricht, Netherlands.ORCID 0000-0002-9858-0802
Niels H ChavannesDepartment of Public Health and Primary Care, Leiden University Medical Centre, Leiden, Netherlands.ORCID 0000-0002-8607-9199
Leiden University · NLMaastricht University · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChronic kidney disease (CKD) poses a major challenge to public health. In CKD patients, adequate disease self-management has been shown to improve both proximal and distal outcomes. Currently, electronic health (eHealth) interventions are increasingly used to optimize patients' self-management skills.

objectiveThis study aimed to systematically review the existing evidence regarding the implementation and effectiveness of eHealth self-management interventions for patients with CKD.

methodsFollowing a search in 8 databases (up to November 2017), quantitative and qualitative data on process and effect outcomes were extracted from relevant studies. Quality was appraised using the Crowe Critical Appraisal Tool; narrative synthesis was performed to analyze the data extracted.

resultsOf the 3307 articles retrieved, 24 (comprising 23 studies) were included in this review; of these, almost half were appraised to be of low to moderate quality. There was considerable heterogeneity in the types of interventions used and the outcomes measured. A total of 10 effect and 9 process outcome indicators were identified. The most frequently reported effect outcome indicators were specific laboratory tests and blood pressure (BP), whereas satisfaction was the most frequently reported process outcome indicator. Positive effects were found for proximal outcomes (eg, BP control and medication adherence), and mixed effects were found for more distal outcomes (eg, quality of life). High feasibility, usability, and acceptability of and satisfaction with eHealth self-management interventions were reported. The determinant ability of health care professionals to monitor and, if necessary, anticipate on patient measurements online was mostly cited to influence patients' adherence to interventions.

conclusionseHealth self-management interventions have the potential to improve disease management and health outcomes. To broaden the evidence base and facilitate intervention upscaling, more detailed descriptions and thorough analysis of the intervention components used are required. In addition, our review reveals that outcomes closely related to the scope and duration of the intervention implemented are most likely to be impacted. For instance, if a 4-week Web-based training to optimize disease management skills is implemented, the outcome perceived control would more likely be affected than kidney function. Although this seems obvious, most studies evaluate only distal outcomes and thereby fail to capture intervention effects that might contribute to long-term health improvement. We advise future researchers to carefully consider their choice of outcomes based on their sensitivity for change. In this way, we ensure that relevant effects are captured and legitimate conclusions are drawn.

Indexed as

HumansMedication AdherenceQuality of LifeRenal Insufficiency, ChronicSelf-ManagementTelemedicinechronic kidney diseaseeHealthself-managementsystematic review

Identifiers

PMID31687937
PMCPMC6864489
OpenAlexW2969431364

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.