Evidence map›Paper›PMID 34499036›Full record

ArticleJMIR diabetes2021

Comparison of Communication Channels for Large-Scale Type 2 Diabetes Risk Screening and Intervention Recruitment: Empirical Study.

Kari Jalkanen, Riia Järvenpää, Tanja Tilles-Tirkkonen, Janne Martikainen, Emma Aarnio, Reija Männikkö, Eeva Rantala, Leila Karhunen, Marjukka Kolehmainen, Marja Harjumaa and 8 more

Abstract read
In one paragraph

Article in JMIR diabetes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

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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

18 authors.

Kari Jalkanen *School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.ORCID 0000-0003-4497-5371
Riia Järvenpää *Department of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland.ORCID 0000-0003-3645-7726
Tanja Tilles-TirkkonenSchool of Medicine, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.ORCID 0000-0002-8268-3401
Janne MartikainenSchool of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.ORCID 0000-0003-0855-3921
Emma AarnioSchool of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.ORCID 0000-0002-6555-7833
Reija MännikköSchool of Medicine, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.ORCID 0000-0002-1448-1971
Eeva RantalaDepartment of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland.ORCID 0000-0001-8512-6638
Leila KarhunenDepartment of Medicine, Endocrinology and Clinical Nutrition, Kuopio University Hospital, Kuopio, Finland.ORCID 0000-0001-5801-8041
Marjukka KolehmainenSchool of Medicine, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.ORCID 0000-0002-3770-2538
Marja HarjumaaVTT Technical Research Centre of Finland Ltd, Espoo, Finland.ORCID 0000-0002-5919-5709
Kaisa PoutanenVTT Technical Research Centre of Finland Ltd, Espoo, Finland.ORCID 0000-0002-2284-4162
Miikka ErmesVTT Technical Research Centre of Finland Ltd, Espoo, Finland.ORCID 0000-0003-4849-9931
Pilvikki AbsetzSchool of Medicine, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.ORCID 0000-0002-1047-909X
Ursula SchwabSchool of Medicine, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.ORCID 0000-0003-1838-7525
Timo LakkaSchool of Medicine, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.ORCID 0000-0002-9199-2871
Jussi PihlajamäkiSchool of Medicine, Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland.ORCID 0000-0002-6241-6859
Jaana LindströmDepartment of Public Health Solutions, Finnish Institute for Health and Welfare, Helsinki, Finland.ORCID 0000-0001-9255-020X
StopDia Study Group *See Acknowledgments, .

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClinical trials have shown that type 2 diabetes (T2D) is preventable through lifestyle interventions targeting high-risk people. Nevertheless, large-scale implementation of risk identification followed by preventive interventions has proven to be challenging. Specifically, recruitment of participants into preventive interventions is an important but often overlooked part of the intervention.

objectiveThis study aims to compare the reach and yield of different communication channels to engage people at increased risk of T2D to fill in a digital screening questionnaire, with emphasis on reaching those at most risk. The participants expressing their willingness to participate is the final step in the risk screening test, and we aim to determine which channels had the most participants reach this step.

methodsWe established a stepwise web-based T2D risk screening tool with automated feedback according to the T2D risk level and, for those who were eligible, an invitation to participate in the StopDia prevention intervention study conducted in a primary health care setting. The risk estimate was based on the Finnish Diabetes Risk Score; history of repeatedly measured high blood glucose concentration; or, among women, previous gestational diabetes. We used several channels to invite people to the StopDia web-based screening tool, and respondents were classified into 11 categories based on the channel through which they reported having learned about StopDia. The demographics of respondents reached via different communication channels were compared using variance analysis. Logistic regression was used to study the respondents' likelihood of progressing through risk screening steps.

resultsA total of 33,399 persons started filling the StopDia screening tool. Of these, 86.13% (28,768/33,399) completed the test and named at least one communication channel as the source of information about StopDia. Altogether, 26,167 persons filled in sufficient information to obtain risk estimates. Of them, 53.22% (13,925/26,167) were at increased risk, 30.06% (7866/26,167) were men, and 39.77% (10,136/25,485) had low or middle education levels. Most frequently mentioned channels were workplace (n=6817), social media or the internet (n=6712), and newspapers (n=4784). The proportion of individuals at increased risk was highest among those reached via community pharmacies (415/608, 68.3%) and health care (1631/2535, 64.33%). The communication channel reaching the largest percentage of interested and eligible men (1353/3979, 34%) was relatives or friends. Health care (578/1069, 54.07%) and radio or television (225/487, 46.2%) accounted for the largest proportion of people with lower education.

conclusionsCommunication channels reaching a large number of people, such as social media and newspapers, were the most effective channels for identifying at-risk people. Personalized approaches increased the engagement of men and less-educated people. Community pharmacies and health care services reached people with a particularly high T2D risk. Thus, communication and recruitment channels should be selected and modified based on the intended target group. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s12889-019-6574-y.

Indexed as

communicationdigital toolmobile phonepreventionpublic health campaignrisk identificationscreeningsocial mediastudy recruitmenttype 2 diabetes

Identifiers

PMID34499036
PMCPMC8461532

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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.