MétaCan
Menu
Back to cohort
Record W3133739951 · doi:10.2196/25016

Communication Intervention Using Digital Technology to Facilitate Informed Choices at Childbirth in the Context of the COVID-19 Pandemic: Protocol for a Randomized Controlled Trial

2021· article· en· W3133739951 on OpenAlexvenueno aff
Carmen Simone Grilo Diniz, Ana Carolina Arruda Franzon, Beatriz Fioretti-Foschi, Denise Yoshie Niy, Livia Sanches Pedrilio, Edson Amaro, João Ricardo Sato

Bibliographic record

VenueJMIR Research Protocols · 2021
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Impact on Reproduction
Canadian institutionsnot available
Fundersnot available
KeywordsChildbirthContext (archaeology)Randomized controlled trialInformed consentPsychological interventionMedicineIntervention (counseling)NursingNeglectPsychologyPregnancyAlternative medicine

Abstract

fetched live from OpenAlex

BACKGROUND: In Brazil and other low- and middle-income countries, excess interventions in childbirth are associated with an increase in preterm and early-term births, contributing to stagnant morbidity and mortality of mothers and neonates. The fact that women often report a negative experience with vaginal childbirth, with physical pain and feelings of unsafety, neglect, or abuse, may explain the high acceptability of elective cesarean sections. The recognition of information needs and of the right to informed choice during childbirth can help change this reality. The internet has been the main source of health information, but its quality is highly variable. OBJECTIVE: This study aimed to develop and evaluate an information and communication strategy through a smartphone app with respect to childbirth, to facilitate informed choices for access to safer and evidence-based care in the context of the COVID-19 pandemic. METHODS: A randomized controlled trial, with 2 arms (intervention and control) and a closed, blind, parallel design, will be conducted with a smartphone app designed for behavior and opinion research in Brazil, with women of reproductive age previously registered on the app. After completing an entry questionnaire to verify the eligibility criteria and obtaining ethical consent, approximately 20,000 participants will be randomly allocated to the intervention and control groups at a 1:1 ratio. Participants allocated to the intervention group will be invited to engage in a digital information and communication strategy, which is designed to expand evidence-based knowledge on the advantages and disadvantages of options for labor and childbirth and the safety of the care processes. The information is based on the guidelines of the Ministry of Health and the World Health Organization for a positive childbirth experience and has been updated to include the new challenges and disruptions in maternity care within the context of the COVID-19 pandemic. The control group will receive information regarding disposable and reusable diapers as a placebo intervention. The groups will be compared in their responses in generating the birth plan and the entry and exit questionnaires, regarding responses less or more aligned with the guidelines for a positive childbirth experience. A qualitative component to map information needs is included. RESULTS: The digital trial started recruiting participants in late October 2020, and data collection has been projected to be complete by December 2020. CONCLUSIONS: This study will evaluate an innovative intervention that has the potential to promote better communication between women and providers, such that they can make better choices using an approach suitable for use during the COVID-19 pandemic. TRIAL REGISTRATION: The Brazilian Clinical Trials Registry U1111-1255-8683; http://www.ensaiosclinicos.gov.br/rg/RBR-3g5f9f/. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/25016.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Randomized triallow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Randomized trialhigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.048
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.127
Threshold uncertainty score0.960

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.048
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.390
GPT teacher head0.603
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Research ProtocolsSame topicCOVID-19 Impact on ReproductionFrench-language works237,207