Evidence map›Paper›PMID 30678684›Full record

ArticleBMC medical informatics and decision making2019

Exploring the role of competing demands and routines during the implementation of a self-management tool for type 2 diabetes: a theory-based qualitative interview study.

Sebastian Potthoff, Justin Presseau, Falko F Sniehotta, Matthew Breckons, Amy Rylance, Leah Avery

Registry-linked trialAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06576323 (An Intervention Mapping Approach to Closing the Gap in Maternal OUD and Infant NAS Care), which is not on this map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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.

NCT06576323 narecruitingnot on this mapstarted 2024, after this paper: background citation

An Intervention Mapping Approach to Closing the Gap in Maternal OUD and Infant NAS Care

TypeinterventionalSponsorUniversity of PennsylvaniaRan2024 to 2027Enrolled50ConditionsOpioid Use Disorder, Neonatal Abstinence SyndromeArmsAn implementation model for co-located Medications for Opioid Use Disorder (MOUD) prescription in the NICU
3 · Its place in the literature

Who cites it

9 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

6 authors.

Sebastian PotthoffFaculty of Health and Life Sciences, Northumbria University, Newcastle Upon Tyne, NE7 7TR, UK. sebastian.potthoff@northumbria.ac.uk.ORCID 0000-0003-4580-8532
Justin PresseauClinical Epidemiology Program, Ottawa Hospital Research Institute, 501 Smyth Road, Ottawa, K1H 8L6, Canada.
Falko F SniehottaNIHR Policy Research Unit Behavioural Science, Newcastle University, The Baddiley-Clark Building, Richardson Road, Newcastle Upon Tyne, NE2 4AX, UK.
Matthew BreckonsInstitute of Health and Society, Newcastle University, Newcastle Upon Tyne, NE2 4AX, UK.
Amy RylanceDiabetes UK, London, UK.
Leah AverySchool of Health & Social Care, Teesside University, Middlesbrough, TS1 3BA, UK.

Funding

British Heart FoundationCancer Research UKMedical Research Council MR/K02325X/1
6 · The paper itself

Abstract

backgroundThe implementation of new medical interventions into routine care involves healthcare professionals adopting new clinical behaviours and changing existing ones. Whilst theory-based approaches can help understand healthcare professionals' behaviours, such approaches often focus on a single behaviour and conceptualise its performance in terms of an underlying reflective process. Such approaches fail to consider the impact of non-reflective influences (e.g. habit and automaticity) and how the myriad of competing demands for their time may influence uptake. The current study aimed to apply a dual process theoretical approach to account for reflective and automatic determinants of healthcare professional behaviour while integrating a multiple behaviour approach to understanding the implementation and use of a new self-management tool by healthcare professionals in the context of diabetes care.

methodsFollowing Diabetes UK's national release of the 'Information Prescription' (DUK IP; a self-management tool targeting the management of cholesterol, blood pressure and HbA1c) in January 2015, we conducted semi-structured interviews with 13 healthcare professionals (general practitioners and nurses) who had started to use the DUK IP during consultations to provide self-management advice to people with type 2 diabetes. A theory-based topic guide included pre-specified constructs from a previously developed logic model. We elicited healthcare professionals' views on reflective processes (outcome expectations, self-efficacy, intention, action and coping planning), automatic processes (habit), and multiple behaviour processes (goal priority, goal conflict and goal facilitation). All interviews were audio recorded and transcribed verbatim and all transcripts were independently double coded and analysed using content analysis.

resultsThe majority of healthcare professionals interviewed reported strong intentions to use the DUK IP and having formed a habit of using them after a minimum of one month continuous use. Pop-up cues in the electronic patient records were perceived to facilitate the use of the tool. Factors that conflicted with the use of the DUK IP included existing pathways of providing self-management advice.

conclusionData suggests that constructs from dual process and multiple behaviour approaches are useful to provide supplemental understanding of the implementation of new self-management tools such as the DUK IP and may help to advance behavioural approaches to implementation science.

Indexed as

Implementation ScienceMedical Informatics ApplicationsAdultDiabetes Mellitus, Type 2FemaleGeneral PractitionersHumansMaleMiddle AgedNursesQualitative ResearchSelf-ManagementAutomaticityDual processHabitHealthcare professionalsInformation prescriptionIntentionPrimary careRoutinesSecondary careType 2 diabetes

Identifiers

PMID30678684
PMCPMC6345053

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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.