Evidence map›Paper›PMID 32635919›Full record

ArticleBMC medical informatics and decision making2020

Differential influences of social support on app use for diabetes self-management - a mixed methods approach.

Nicola Brew-Sam, Arul Chib, Constanze Rossmann

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

3 authors.

Nicola Brew-SamDepartment of Health Services Research and Policy, Research School of Population Health, College of Health and Medicine, Australian National University, Mills Rd, Acton ACT 2601, Canberra, Australia.
Arul ChibWee Kim Wee School of Communication and Information, Nanyang Technological University, 31 Nanyang Link, Singapore, 637718, Singapore. ArulChib@ntu.edu.sg.ORCID 0000-0002-3833-8889
Constanze RossmannDepartment of Media and Communication Studies, University of Erfurt, Nordhaeuser Str. 63, 99089, Erfurt, Germany.

Funding

Nanyang Technological University M4081081
6 · The paper itself

Abstract

backgroundRecent studies increasingly examine social support for diabetes self-management delivered via mHealth. In contrast to previous studies examining social support as an outcome of technology use, or technology as a means for delivering social support, this paper argues that social support has an impact on the use of diabetes mHealth apps. Specifically, we postulate differences between the impact of healthcare professional versus non-professional (family/friends) support on mobile app use for diabetes self-management.

methodsThis research employed a triangulation of methods including exploratory semi-structured face-to-face interviews (N = 21, Study 1) and an online survey (N = 65, Study 2) with adult type 1 and type 2 diabetes patients. Thematic analysis (Study 1) was used to explore the relevance of social support (by professionals versus non-professionals) for diabetes app use. Binary logistic regression (Study 2) was applied to compare healthcare decision-making, healthcare-patient communication, and the support by the personal patient network as predictors of diabetes app use, complemented by other predictors from self-management and technology adoption theory.

resultsThe interviews (Study 1) demonstrated that (technology-supported) shared decision-making and supportive communication by healthcare professionals depended on their medical specialty. The personal patient network was perceived as either facilitating or hindering the use of mHealth for self-management. Binary logistic regression (Study 2) showed that the physician specialty significantly predicted the use of diabetes apps, with supervision by diabetes specialists increasing the likelihood of app use (as opposed to general practitioners). Additionally, specialist care positively related to a higher chance of shared decision-making and better physician-patient communication. The support by the personal patient network predicted diabetes app use in the opposite direction, with less family/friend support increasing the likelihood of app use.

conclusionThe results emphasize the relevance of support by healthcare professionals and by the patient network for diabetes app use and disclose differences from the existing literature. In particular, the use of diabetes apps may increase in the absence of social support by family or friends (e.g., compensation for lack of support), and may decrease when such support is high (e.g., no perceived need to use technology).

Indexed as

Diabetes MellitusMobile ApplicationsSelf-ManagementAdultAgedCross-Sectional StudiesFemaleHumansMaleMiddle AgedSocial SupportAppsDiabetesmHealthSelf-managementShared decision-makingSocial supportTechnology

Identifiers

PMID32635919
PMCPMC7341589

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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.