Evidence map›Paper›PMID 30664466›Full record

ArticleJournal of medical Internet research2019

Digital Recruitment and Acceptance of a Stepwise Model to Prevent Chronic Disease in the Danish Primary Care Sector: Cross-Sectional Study.

Lars Bruun Larsen, Jens Sondergaard, Janus Laust Thomsen, Anders Halling, Anders Larrabee Sønderlund, Jeanette Reffstrup Christensen, Trine Thilsing

Open access · goldAbstract read
In one paragraph

Article 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 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

8 citing papers in PubMed, 15 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

7 authors at 3 institutions in 2 countries.

Lars Bruun LarsenResearch Unit of General Practice, Institute of Public Health, University of Southern Denmark, Odense, Denmark.ORCID 0000-0001-9120-4751
Jens SondergaardResearch Unit of General Practice, Institute of Public Health, University of Southern Denmark, Odense, Denmark.ORCID 0000-0002-1629-1864
Janus Laust ThomsenResearch Unit for General Practice, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.ORCID 0000-0002-0745-6815
Anders HallingDepartment of Clinical Sciences in Malmö, Centre for Primary Health Care Research, Lund University, Lund, Sweden.ORCID 0000-0002-1035-7586
Anders Larrabee SønderlundResearch Unit of General Practice, Institute of Public Health, University of Southern Denmark, Odense, Denmark.ORCID 0000-0002-6627-3322
Jeanette Reffstrup ChristensenResearch Unit of General Practice, Institute of Public Health, University of Southern Denmark, Odense, Denmark.ORCID 0000-0002-2412-5989
Trine ThilsingResearch Unit of General Practice, Institute of Public Health, University of Southern Denmark, Odense, Denmark.ORCID 0000-0002-2041-2219
University of Southern Denmark · DKAalborg University · DKLund University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDuring recent years, stepwise approaches to health checks have been advanced as an alternative to general health checks. In 2013, we set up the Early Detection and Prevention project (Tidlig Opsporing og Forebyggelse, TOF) to develop a stepwise approach aimed at patients at high or moderate risk of a chronic disease. A novel feature was the use of a personal digital mailbox for recruiting participants. A personal digital mailbox is a secure digital mailbox provided by the Danish public authorities. Apart from being both safe and secure, it is a low-cost, quick, and easy way to reach Danish residents.

objectiveIn this study we analyze the association between the rates of acceptance of 2 digital invitations sent to a personal digital mailbox and the sociodemographic determinants, medical treatment, and health care usage in a stepwise primary care model for the prevention of chronic diseases.

methodsWe conducted a cross-sectional analysis of the rates of acceptance of 2 digital invitations sent to randomly selected residents born between 1957 and 1986 and residing in 2 Danish municipalities. The outcome was acceptance of the 2 digital invitations. Statistical associations were determined by Poisson regression. Data-driven chi-square automatic interaction detection method was used to generate a decision tree analysis, predicting acceptance of the digital invitations.

resultsA total of 8814 patients received an invitation in their digital mailbox from 47 general practitioners. A total of 40.22% (3545/8814) accepted the first digital invitation, and 30.19 % (2661/8814) accepted both digital invitations. The rates of acceptance of both digital invitations were higher among women, older patients, patients of higher socioeconomic status, and patients not diagnosed with or being treated for diabetes mellitus, chronic obstructive pulmonary disease, or cardiovascular disease.

conclusionsTo our knowledge, this is the first study to report on the rates of acceptance of digital invitations to participate in a stepwise model for prevention of chronic diseases. More studies of digital invitations are needed to determine if the acceptance rates seen in this study should be expected from future studies as well. Similarly, more research is needed to determine whether a multimodal recruitment approach, including digital invitations to personal digital mailboxes will reach hard-to-reach subpopulations more effectively than digital invitations only.

Indexed as

Chronic DiseaseCross-Sectional StudiesDenmarkFemaleHealth PromotionHumansMaleMiddle AgedPrimary Health Careclinical decision support systemscross-sectional studiespromotion of health

Identifiers

PMID30664466
PMCPMC6360391
OpenAlexW2911539515

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.