Evidence map›Paper›PMID 34734832›Full record

ReviewJournal of medical Internet research2021

The Sociological Perspective of Users' Invisible Work: A Qualitative Research Framework for Studying Digital Health Innovations Integration.

Dilara Vanessa Trupia, Alexandre Mathieu-Fritz, Tu Anh Duong

Abstract readReview
In one paragraph

Review in Journal of medical Internet research, 2021. 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
–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

8 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

3 authors.

Dilara Vanessa TrupiaLATTS, Univ Gustave Eiffel, CNRS, Ecole des Ponts, Marne-la-Vallée, France.ORCID 0000-0003-0538-0068
Alexandre Mathieu-FritzLATTS, Univ Gustave Eiffel, CNRS, Ecole des Ponts, Marne-la-Vallée, France.ORCID 0000-0002-3878-2648
Tu Anh DuongINSERM, Chaire Avenir Santé Numérique IMRB U955, Équipe 8, University of Paris-Est Créteil, Créteil, France.ORCID 0000-0003-2221-9903

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWhen new technology is integrated into a care pathway, it faces resistance due to the changes it introduces into the existing context. To understand the success or failure of digital health innovations, it is necessary to pay attention to the adjustments that users must perform to make them work, by reshaping the context and sometimes by altering the ways in which they perform activities. This adaptation work, most of which remains invisible, constitutes an important factor in the success of innovations and the ways in which they transform care practices.

objectiveThis work aims to present a sociological framework for studying new health technology uses through a qualitative analysis of the different types of tasks and activities that users, both health professionals and patients, must perform to integrate these technologies and make them work in their daily routine.

methodsThis paper uses a three-part method to structure a theoretical model to study users' invisible work. The first part of the method includes a thematic literature review, previously published by one of the coauthors, of major sociological studies conducted on digital health innovations integration into existing care organizations and practices. The second part extends this review to introduce definitions and applications of the users' invisible work concept. The third part consists of producing a theoretical framework to study the concept according to the different contexts and practices of the users.

resultsThe paper proposes four dimensions (organizational, interactional, practical, and experiential), each composed of a set of criteria that allow a comparative analysis of different users' work according to different health technologies.

conclusionsThis framework can be applied both as an analytical tool in a research protocol and as an agenda to identify less visible adoption criteria for digital health technologies.

Indexed as

Health PersonnelTechnologyDiagnostic Tests, RoutineHumansQualitative Researchchronic illnessdigital health innovationsinvisible workparticipatory health carepatient workqualitative analysisself-quantificationsociological frameworkuser work

Identifiers

PMID34734832
PMCPMC8603174

What OpenQuestion holds

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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.