Evidence map›Paper›PMID 37725413›Full record

ArticleJournal of medical Internet research2023

Digital Health Implementation Strategies Coproduced With Adults With Acquired Brain Injury, Their Close Others, and Clinicians: Mixed Methods Study With Collaborative Autoethnography and Network Analysis.

Melissa Miao, Rosemary Morrow, Alexander Salomon, Ben Mcculloch, Jean-Christophe Evain, Meg Rebecca Wright, Marie Therese Murphy, Monica Welsh, Liz Williams, Emma Power and 4 more

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
5.4field-weighted citation impact, top 4% 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

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. 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

14 authors at 3 institutions in 1 country.

Melissa MiaoGraduate School of Health, Faculty of Health, University of Technology Sydney, Sydney, Australia.ORCID 0000-0002-4113-0149
Rosemary MorrowStakeholder with living experience of acquired brain injury, Sydney, Australia.ORCID 0000-0002-8622-9230
Alexander SalomonStakeholder with living experience of acquired brain injury, Sydney, Australia.ORCID 0000-0002-5110-725X
Ben MccullochStakeholder with living experience of acquired brain injury, Sydney, Australia.ORCID 0000-0003-1626-7538
Jean-Christophe EvainAcquired Brain Injury Rehabilitation Ward, Caulfield Hospital, Alfred Health Network, Melbourne, Australia.ORCID 0000-0002-0196-8203
Meg Rebecca WrightStakeholder with living experience of acquired brain injury, Blenheim, Australia.ORCID 0000-0002-4581-7087
Marie Therese MurphyStakeholder with living experience as a communication partner of a person with acquired brain injury, Sydney, Australia.ORCID 0000-0003-0234-0001
Monica WelshBrain Injury Rehabilitation Unit, South Australian Brain Injury Rehabilitation Service, Adelaide, Australia.ORCID 0000-0003-2097-3638
Liz WilliamsBrain Injury Rehabilitation Community and Home (BIRCH), South Australian Brain Injury Rehabilitation Service, Adelaide, Australia.ORCID 0000-0003-2540-0898
Emma PowerGraduate School of Health, Faculty of Health, University of Technology Sydney, Sydney, Australia.ORCID 0000-0002-2638-0406
Rachael RietdijkFaculty of Medicine and Health, The University of Sydney, Sydney, Australia.ORCID 0000-0003-4343-4039
Deborah DebonoSchool of Public Health, Faculty of Health, University of Technology Sydney, Sydney, Australia.ORCID 0000-0003-2095-156X
Melissa BrunnerFaculty of Medicine and Health, The University of Sydney, Sydney, Australia.ORCID 0000-0001-6823-5189
Leanne TogherFaculty of Medicine and Health, The University of Sydney, Sydney, Australia.ORCID 0000-0002-4518-6748
The University of Sydney · AUUniversity of Technology Sydney · AUCaulfield Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcquired brain injuries (ABIs), such as stroke and traumatic brain injury, commonly cause cognitive-communication disorders, in which underlying cognitive difficulties also impair communication. As communication is an exchange with others, close others such as family and friends also experience the impact of cognitive-communication impairment. It is therefore an internationally recommended best practice for speech-language pathologists to provide communication support to both people with ABI and the people who communicate with them. Current research also identifies a need for neurorehabilitation professionals to support digital communication, such as social media use, after ABI. However, with >135 million people worldwide affected by ABI, alternate and supplementary service delivery models are needed to meet these communication needs. The "Social Brain Toolkit" is a novel suite of 3 interventions to deliver communication rehabilitation via the internet. However, digital health implementation is complex, and minimal guidance exists for ABI.

objectiveThis study aimed to support the implementation of the Social Brain Toolkit by coproducing implementation knowledge with people with ABI, people who communicate with people with ABI, clinicians, and leaders in digital health implementation.

methodsA maximum variation sample (N=35) of individuals with living experience of ABI, close others, clinicians, and digital health implementation leaders participated in an explanatory sequential mixed methods design. Stakeholders quantitatively prioritized 4 of the 7 theoretical domains of the Nonadoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework as being the most important for Social Brain Toolkit implementation. Qualitative interview and focus group data collection focused on these 4 domains. Data were deductively analyzed against the NASSS framework with stakeholder coauthors to determine implementation considerations and strategies. A collaborative autoethnography of the research was conducted. Interrelationships between considerations and strategies were identified through a post hoc network analysis.

resultsAcross the 4 prioritized domains of "condition," "technology," "value proposition," and "adopters," 48 digital health implementation considerations and 52 tailored developer and clinician implementation strategies were generated. Benefits and challenges of coproduction were identified. The post hoc network analysis revealed 172 unique relationships between the identified implementation considerations and strategies, with user and persona testing and responsive design identified as the potentially most impactful strategies.

conclusionsPeople with ABI, close others, clinicians, and digital health leaders coproduced new knowledge of digital health implementation considerations for adults with ABI and the people who communicate with them, as well as tailored implementation strategies. Complexity-informed network analyses offered a data-driven method to identify the 2 most potentially impactful strategies. Although the study was limited by a focus on 4 NASSS domains and the underrepresentation of certain demographics, the wealth of actionable implementation knowledge produced supports future coproduction of implementation research with mutually beneficial outcomes for stakeholders and researchers. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/35080.

Indexed as

Brain InjuriesBrain Injuries, TraumaticAdultBrainCommunicationData CollectionHumansbrain injurycaregiverscomplexitydelivery of health caredigital healthimplementation scienceinternet interventionsmobile phonepsychosocialpsychosocial interventionsstroketraumatic brain injury

Identifiers

PMID37725413
PMCPMC10548320
OpenAlexW4385521687

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.