Evidence map›Paper›PMID 36510286›Full record

Trial reportTrials2022

CARE 1000: randomized controlled trial for the evaluation of the effectiveness of a mHealth app for supporting the first 1000 days of life.

Laura Brunelli, Sofia Bussolaro, Margherita Dal Cin, Luca Ronfani, Sara Zanchiello, Andrea Cassone, Giuseppa Verardi, Raffaella Dobrina, Michele Bava, Tamara Stampalija

Registry-linked trialAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Trials, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05500339 (CARE 1000. Randomized Control Trial for the Evaluation of the Effectiveness of a mHealth App for Supporting the First 1000 Days of Life), which is not on this map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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.

NCT05500339 naunknown statusnot on this map

CARE 1000. Randomized Control Trial for the Evaluation of the Effectiveness of a mHealth App for Supporting the First 1000 Days of Life

TypeinterventionalSponsorIRCCS Burlo GarofoloRan2022 to 2024Enrolled360ConditionsHealth-Related BehaviorArmsM-health App, Standard care
3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

10 authors.

Laura BrunelliDepartment of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy. laura.brunelli@phd.units.it.ORCID http://orcid.org/0000-0002-5475-0021
Sofia BussolaroDepartment of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy.
Margherita Dal CinDepartment of Prevention, Giuliano Isontina Healthcare University Trust, Trieste, Italy.
Luca RonfaniClinical Epidemiology and Healthcare Services Research, Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy.
Sara ZanchielloArea Science Park, Trieste, Italy.
Andrea CassoneHealthcare Professions Department, Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy.
Giuseppa VerardiHealthcare Professions Department, Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy.
Raffaella DobrinaHealthcare Professions Department, Institute for Maternal and Child Health - IRCCS "Burlo Garofolo", Trieste, Italy.
Michele BavaDepartment of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy.
Tamara StampalijaDepartment of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRecent developments in eHealth and mobile health (mHealth), as well as the introduction of information and communication technology innovations in clinical practice, such as telemedicine, telemonitoring, and remote examinations, are already changing the current scenario and will continue to generate innovations in the coming decades. The widespread use of mobile devices, with an estimated nearly 30 billion devices and more than 325,000 apps worldwide, will provide various opportunities for people to take control of their own health. Already in 2017, most of the apps available were focused on pregnancy support, more than any other medical field. There have been some reported experiences with social media and mHealth that could benefit the promotion of maternal physical and mental health during pregnancy. However, many apps targeting the first 1000 days of a child's life do not consider the continuity between the prenatal and postnatal periods and their joint impact on maternal and child health. The aim of this study is to evaluate the effectiveness of this mHealth app to support women during the first 1000 days (from conception to 24 months of age) and to improve health prevention behaviours such as immunizations during pregnancy, weight gain during pregnancy, abstinence from smoking and alcohol consumption, and adherence to the routine childhood immunization schedule. In addition, the study aims to understand the level of appreciation of this mHealth app as a tool to overcome information and communication gaps between patients and institutions.

methodsConduction of a randomized controlled trial. DISCUSSION: Our results will be relevant for improving this mHealth app to promote health and prevention and to support the first 1000 days of life for both mother and child. Our results will be relevant to the future expansion of such an mHealth app to promote positive health-related outcomes in patients and co-user satisfaction and to support the organization of health services.

trial registrationClinicalTrials.gov NCT05500339.

Indexed as

Mobile ApplicationsTelemedicineChildCommunicationFemaleHealth PromotionHumansPregnancyFirst 1000 daysHealth preventionmHealth

Identifiers

PMID36510286
PMCPMC9744031

What OpenQuestion holds

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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.