Evidence map›Paper›PMID 35776437›Full record

ArticleJMIR human factors2022

The Influencing Contexts and Potential Mechanisms Behind the Use of Web-Based Self-management Support Interventions: Realistic Evaluation.

Marscha Engelen, Betsie van Gaal, Hester Vermeulen, Rixt Zuidema, Sebastian Bredie, Sandra van Dulmen

Open access · goldAbstract read
In one paragraph

Article in JMIR human factors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.3field-weighted citation impact, top 42% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 2 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. 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 3 institutions in 2 countries.

Marscha EngelenIQ Healthcare, Radboud Institute for Health Sciences, Radboud university medical center, Nijmegen, Netherlands.ORCID https://orcid.org/0000-0001-8685-1516
Betsie van GaalIQ Healthcare, Radboud Institute for Health Sciences, Radboud university medical center, Nijmegen, Netherlands.ORCID https://orcid.org/0000-0001-8884-6235
Hester VermeulenIQ Healthcare, Radboud Institute for Health Sciences, Radboud university medical center, Nijmegen, Netherlands.ORCID https://orcid.org/0000-0002-0743-2979
Rixt ZuidemaResearch Group Proactive Care for Older People, Faculty of Health Care, University of Applied Sciences Utrecht, Utrecht, Netherlands.ORCID https://orcid.org/0000-0003-0396-2654
Sebastian BredieDivision of Vascular Medicine, Department of Internal Medicine, Radboud university medical center, Nijmegen, Netherlands.ORCID https://orcid.org/0000-0002-6973-7540
Sandra van DulmenDepartment of Primary and Community Care, Radboud Institute for Health Sciences, Radboud university medical center, Nijmegen, Netherlands.ORCID https://orcid.org/0000-0002-1651-7544
Radboud University Nijmegen · NLHAN University of Applied Sciences · NLUniversity of Applied Sciences Utrecht · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSelf-management can increase self-efficacy and quality of life and improve disease outcomes. Effective self-management may also help reduce the pressure on health care systems. However, patients need support in dealing with their disease and in developing skills to manage the consequences and changes associated with their condition. Web-based self-management support programs have helped patients with cardiovascular disease (CVD) and rheumatoid arthritis (RA), but program use has been low.

objectiveThis study aimed to identify the patient, disease, and program characteristics that determine whether patients use web-based self-management support programs or not.

methodsA realistic evaluation methodology was used to provide a comprehensive overview of context (patient and disease characteristics), mechanism (program characteristics), and outcome (program use). Secondary data of adult patients with CVD (n=101) and those with RA (n=77) were included in the study. The relationship between context (sex, age, education, employment status, living situation, self-management [measured using Patient Activation Measure-13], quality of life [measured using RAND 36-item health survey], interaction efficacy [measured using the 5-item perceived efficacy in patient-physician interactions], diagnosis, physical comorbidity, and time since diagnosis) and outcome (program use) was analyzed using logistic regression analyses. The relationship between mechanism (program design, implementation strategies, and behavior change techniques [BCTs]) and outcome was analyzed through a qualitative interview study.

resultsThis study included 68 nonusers and 111 users of web-based self-management support programs, of which 56.4% (101/179) were diagnosed with CVD and 43.6% (78/179) with RA. Younger age and a lower level of education were associated with program use. An interaction effect was found between program use and diagnosis and 4 quality of life subscales (social functioning, physical role limitations, vitality, and bodily pain). Patients with CVD with higher self-management and quality of life scores were less likely to use the program, whereas patients with RA with higher self-management and quality of life scores were more likely to use the program. Interviews with 10 nonusers, 10 low users, and 18 high users were analyzed to provide insight into the relationship between mechanisms and outcome. Program use was encouraged by an easy-to-use, clear, and transparent design and by recommendations from professionals and email reminders. A total of 5 BCTs were identified as potential mechanisms to promote program use: tailored information, self-reporting behavior, delayed feedback, providing information on peer behavior, and modeling.

conclusionsThis realistic evaluation showed that certain patient, disease, and program characteristics (age, education, diagnosis, program design, type of reminder, and BCTs) are associated with the use of web-based self-management support programs. These results represent the first step in improving the tailoring of web-based self-management support programs. Future research on the interaction between patient and program characteristics should be conducted to improve the tailoring of participants to program components.

Indexed as

cardiovascular diseaseschronic diseasepatient dropoutsprogram userealistic evaluationrheumatoid arthritisself-managementtelemedicine

Identifiers

PMID35776437
PMCPMC9288100
OpenAlexW4283779280

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.