2021
DOI: 10.1186/s12910-020-00568-1
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Lay persons’ perception of the requirements for research in emergency obstetric and newborn care

Abstract: Background Factors that could potentially act as facilitators and barriers to successful recruitment strategies in perinatal clinical trials are not well documented. The objective was to assess lay persons’ understanding of the informed consent for randomized clinical trial in emergency obstetric and newborn care. Methods This was a qualitative study conducted among survivors of severe obstetric complications who were attending the post-natal clin… Show more

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Cited by 13 publications
(8 citation statements)
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References 40 publications
(47 reference statements)
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“…1- Reading and re-reading each transcribed interview, 2- Extracting important terms and phrases from the transcripts, 3- Assigning meaning to the extracted units, 4- Organizing and categorizing similar units, 5- Presenting comprehensive descriptions of the extracted categories, 6- Creating a basic paradigm of the subject under study according to the extracted categories, 7- Confirming the basic paradigm by having the participants verify the themes and categories [ 17 ]. An example of an analysis is outlined in Table 1 .…”
Section: Methodsmentioning
confidence: 99%
“…1- Reading and re-reading each transcribed interview, 2- Extracting important terms and phrases from the transcripts, 3- Assigning meaning to the extracted units, 4- Organizing and categorizing similar units, 5- Presenting comprehensive descriptions of the extracted categories, 6- Creating a basic paradigm of the subject under study according to the extracted categories, 7- Confirming the basic paradigm by having the participants verify the themes and categories [ 17 ]. An example of an analysis is outlined in Table 1 .…”
Section: Methodsmentioning
confidence: 99%
“…It means that a patient, logging through a patient interface, is able to choose which elements of her records can be accessed by researchers and for how long. Such digital tools are already applied in research and clinical practice (Shelton 2011 , Wallace and Miola 2021 ). This is in congruence with Neal Dickert’s and his colleagues analysis that distinguishes seven different functions of informed consent.…”
Section: Discussionmentioning
confidence: 99%
“…Using AI for augmentation has been a preferred approach to integrating humans and intelligent machines for collective and supporting decision-making capabilities (Davenport & Kirby, 2015 ). Although AI applications in healthcare have accrued excellent resource efficiency and productivity gains (through automation) and improved quality of work and versatility (through augmentation), they also have raised many ethical concerns, including issues of privacy, security, trust, responsibility, and accountability (Murphy et al, 2021 ). Acknowledging the necessary need for the power of AI and the irreversible tide of its use, many organised and scholarly efforts have been advancing frameworks and strategies (Floridi et al, 2018 , Leslie, 2020 , Murphy et al, 2021 ) to mitigate the ethical concerns posed by the applications of AI in healthcare.…”
Section: Responsible Ai For Digital Health: Literature Taxonomymentioning
confidence: 99%
“…Although AI applications in healthcare have accrued excellent resource efficiency and productivity gains (through automation) and improved quality of work and versatility (through augmentation), they also have raised many ethical concerns, including issues of privacy, security, trust, responsibility, and accountability (Murphy et al, 2021 ). Acknowledging the necessary need for the power of AI and the irreversible tide of its use, many organised and scholarly efforts have been advancing frameworks and strategies (Floridi et al, 2018 , Leslie, 2020 , Murphy et al, 2021 ) to mitigate the ethical concerns posed by the applications of AI in healthcare. Nonetheless, the pandemic has added another complicating factor (urgency) to the discourse on the delicate balance between leveraging AI’s power and mitigating ethical concerns.…”
Section: Responsible Ai For Digital Health: Literature Taxonomymentioning
confidence: 99%
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