Evidence map›Paper›PMID 33112239›Full record

SynthesisJournal of medical Internet research2020

Toward a Digital Platform for the Self-Management of Noncommunicable Disease: Systematic Review of Platform-Like Interventions.

Sarah A Tighe, Kylie Ball, Finn Kensing, Lars Kayser, Jonathan C Rawstorn, Ralph Maddison

2 registry-linked trialsOpen access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 41 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 7 pooled it
8.9field-weighted citation impact, top 2% 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.

NCT06867081 nanot yet recruitingnot on this mapstarted 2025, after this paper: background citation

Effectiveness of a Customized Digital Platform to Increase Coordination of Care and Uptake of Evidence-based Practices: a Protocol for a Stepped-wedge Cluster Randomized Trial in Quebec

TypeinterventionalSponsorCentre for Interdisciplinary Research in Rehabilitation of Greater MontrealRan2025 to 2029Enrolled962ConditionsAquired Brain Injury, Traumatic Brain Injuries, Stroke, Cardiovascular DiseasesArmsThe intervention will be the BRILLIANT Platform, an online platform which provides five Modules aimed at increasing coordination of care and direct rehabilitation time
NCT07345832 narecruitingnot on this mapstarted 2026, after this paper: background citation

The Effect of Volunteer-Engaged Lifestyle Optimisation Via ICOPE on Sarcopenia in Older Adults (VELO-S): A Randomised Controlled Trial

TypeinterventionalSponsorThe University of Hong KongRan2026 to 2027Enrolled200ConditionsSarcopenia, Sarcopenia in Elderly, Fall Prevention in Healthy Aging, Frailty SyndromeArmsVolunteer-Engaged Lifestyle Optimisation via ICOPE for Sarcopenia program (VELO-S), Attention control
3 · Its place in the literature

Who cites it

41 citing papers in PubMed, 7 syntheses or guidelines pooled it, 65 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

6 authors at 2 institutions in 2 countries.

Sarah A TigheInstitute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Burwood, Australia.ORCID 0000-0003-4944-7906
Kylie BallInstitute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Burwood, Australia.ORCID 0000-0003-2893-8415
Finn KensingDepartment of Computer Science, Faculty of Science, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0002-1392-5999
Lars KayserDepartment of Public Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0002-0909-4088
Jonathan C RawstornInstitute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Burwood, Australia.ORCID 0000-0002-9755-7993
Ralph MaddisonInstitute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Burwood, Australia.ORCID 0000-0001-8564-5518
Deakin University · AUUniversity of Copenhagen · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital interventions are effective for health behavior change, as they enable the self-management of chronic, noncommunicable diseases (NCDs). However, they often fail to facilitate the specific or current needs and preferences of the individual. A proposed alternative is a digital platform that hosts a suite of discrete, already existing digital health interventions. A platform architecture would allow users to explore a range of evidence-based solutions over time to optimize their self-management and health behavior change.

objectiveThis review aims to identify digital platform-like interventions and examine their potential for supporting self-management of NCDs and health behavior change.

methodsA literature search was conducted in January 2020 using EBSCOhost, PubMed, Scopus, and EMBASE. No digital platforms were identified, so criteria were broadened to include digital platform-like interventions. Eligible platform-like interventions offered a suite of discrete, evidence-based health behavior change features to optimize self-management of NCDs in an adult population and provided digitally supported guidance for the user toward the features best suited to their needs and preferences. Data collected on interventions were guided by the CONSORT-EHEALTH (Consolidated Standards of Reporting Trials of Electronic and Mobile Health Applications and Online Telehealth) checklist, including evaluation data on effectiveness and process outcomes. The quality of the included literature was assessed using the Mixed Methods Appraisal Tool.

resultsA total of 7 studies were included for review. Targeted NCDs included cardiovascular diseases (CVD; n=3), diabetes (n=3), and chronic obstructive pulmonary disease (n=1). The mean adherence (based on the number of follow-up responders) was 69% (SD 20%). Of the 7 studies, 4 with the highest adherence rates (80%) were also guided by behavior change theories and took an iterative, user-centered approach to development, optimizing intervention relevance. All 7 interventions presented algorithm-supported user guidance tools, including electronic decision support, smart features that interact with patterns of use, and behavior change stage-matching tools. Of the 7 studies, 6 assessed changes in behavior. Significant effects in moderate-to-vigorous physical activity were reported, but for no other specific health behaviors. However, positive behavior change was observed in studies that focused on comprehensive behavior change measures, such as self-care and self-management, each of which addresses several key lifestyle risk factors (eg, medication adherence). No significant difference was found for psychosocial outcomes (eg, quality of life). Significant changes in clinical outcomes were predominately related to disease-specific, multifaceted measures such as clinical disease control and cardiovascular risk score.

conclusionsIterative, user-centered development of digital platform structures could optimize user engagement with self-management support through existing, evidence-based digital interventions. Offering a palette of interventions with an appropriate degree of guidance has the potential to facilitate disease-specific health behavior change and effective self-management among a myriad of users, conditions, or stages of care.

Indexed as

AgedFemaleHumansMaleMiddle AgedNoncommunicable DiseasesPilot ProjectsQuality of LifeSelf-ManagementTelemedicinechronic diseasehealth behaviormobile healthmobile phonenoncommunicable diseasesself-managementweb-based intervention

Identifiers

PMID33112239
PMCPMC7657720
OpenAlexW3097124399

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.