Evidence map›Paper›PMID 35896164›Full record

ArticleJMIR pediatrics and parenting2022

User Experience of a Computer-Based Decision Aid for Prenatal Trisomy Screening: Mixed Methods Explanatory Study.

Titilayo Tatiana Agbadje, Chantale Pilon, Pierre Bérubé, Jean-Claude Forest, François Rousseau, Samira Abbasgholizadeh Rahimi, Yves Giguère, France Légaré

Abstract read
In one paragraph

Article in JMIR pediatrics and parenting, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Titilayo Tatiana AgbadjeVITAM - Centre de recherche en santé durable, Centre intégré universitaire de santé et services sociaux de la Capitale-Nationale, Quebec, QC, Canada.ORCID https://orcid.org/0000-0002-4363-0585
Chantale PilonVITAM - Centre de recherche en santé durable, Centre intégré universitaire de santé et services sociaux de la Capitale-Nationale, Quebec, QC, Canada.ORCID https://orcid.org/0000-0002-0194-0454
Pierre BérubéGreybox Solutions Inc, Montreal, QC, Canada.ORCID https://orcid.org/0000-0003-2570-1770
Jean-Claude ForestDepartment of Molecular Biology, Medical Biochemistry, and Pathology, Faculty of Medicine, Université Laval, Quebec, QC, Canada.ORCID https://orcid.org/0000-0002-5910-5822
François RousseauDepartment of Molecular Biology, Medical Biochemistry, and Pathology, Faculty of Medicine, Université Laval, Quebec, QC, Canada.ORCID https://orcid.org/0000-0002-4504-5507
Samira Abbasgholizadeh RahimiDepartment of Family Medicine, Faculty of Medicine, McGill University, Montreal, QC, Canada.ORCID https://orcid.org/0000-0003-3781-1360
Yves GiguèreDepartment of Molecular Biology, Medical Biochemistry, and Pathology, Faculty of Medicine, Université Laval, Quebec, QC, Canada.ORCID https://orcid.org/0000-0002-8655-1609
France LégaréVITAM - Centre de recherche en santé durable, Centre intégré universitaire de santé et services sociaux de la Capitale-Nationale, Quebec, QC, Canada.ORCID https://orcid.org/0000-0002-2296-6696

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMobile health tools can support shared decision-making. We developed a computer-based decision aid (DA) to help pregnant women and their partners make informed, value-congruent decisions regarding prenatal screening for trisomy.

objectiveThis study aims to assess the usability and usefulness of computer-based DA among pregnant women, clinicians, and policy makers.

methodsFor this mixed methods sequential explanatory study, we planned to recruit a convenience sample of 45 pregnant women, 45 clinicians from 3 clinical sites, and 15 policy makers. Eligible women were aged >18 years and >16 weeks pregnant or had recently given birth. Eligible clinicians and policy makers were involved in prenatal care. We asked the participants to navigate a computer-based DA. We asked the women about the usefulness of the DA and their self-confidence in decision-making. We asked all participants about usability, quality, acceptability, satisfaction with the content of the DA, and collected sociodemographic data. We explored participants' reactions to the computer-based DA and solicited suggestions. Our interview guide was based on the Mobile App Rating Scale. We performed descriptive analyses of the quantitative data and thematic deductive and inductive analyses of the qualitative data for each participant category.

resultsA total of 45 pregnant women, 14 clinicians, and 8 policy makers participated. Most pregnant women were aged between 25 and 34 years (34/45, 75%) and White (42/45, 94%). Most clinicians were aged between 35 and 44 years (5/14, 36%) and women (11/14, 79%), and all were White (14/14, 100%); the largest proportion of policy makers was aged between 45 and 54 years (4/8, 50%), women (5/8, 62%), and White (8/8, 100%). The mean usefulness score for preparing for decision-making for women was 80/100 (SD 13), and the mean self-efficacy score was 88/100 (SD 11). The mean usability score was 84/100 (SD 14) for pregnant women, 77/100 (SD 14) for clinicians, and 79/100 (SD 23) for policy makers. The mean global score for quality was 80/100 (SD 9) for pregnant women, 72/100 (SD 12) for clinicians, and 80/100 (SD 9) for policy makers. Regarding acceptability, participants found the amount of information just right (52/66, 79%), balanced (58/66, 88%), useful (38/66, 58%), and sufficient (50/66, 76%). The mean satisfaction score with the content was 84/100 (SD 13) for pregnant women, 73/100 (SD 16) for clinicians, and 73/100 (SD 20) for policy makers. Participants thought the DA could be more engaging (eg, more customizable) and suggested strategies for implementation, such as incorporating it into clinical guidelines.

conclusionsPregnant women, clinicians, and policy makers found the DA usable and useful. The next steps are to incorporate user suggestions for improving engagement and implementing the computer-based DA in clinical practice.

Indexed as

computer-based decision aidDown syndromemixed methodsprenatal screeningshared decision-makingtrisomy

Identifiers

PMID35896164
PMCPMC9490528

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.