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Record W4408144032 · doi:10.2196/59954

Supplementing Consent for a Prospective Longitudinal Cohort Study of Infants With Antenatal Opioid Exposure: Development and Assessment of a Digital Tool

2025· article· en· W4408144032 on OpenAlexvenueno aff
Jamie E. Newman, Leslie Clarke, Pranav Athimuthu, Megan Dhawan, Sharon Owen, Traci Beiersdorfer, Lindsay Parlberg, Ananta Bangdiwala, Taya McMillan, Sara B. DeMauro, Scott A. Lorch, Myriam Peralta-Carcelén, Deanne E. Wilson-Costello, Namasivayam Ambalavanan, Stephanie L. Merhar, Brenda B. Poindexter, Catherine Limperopoulos, Jonathan M Davis, Michele Walsh, Carla Bann

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsMedicineProspective cohort studyOpioidCohortLongitudinal studyPediatricsCohort studyObstetricsInternal medicine

Abstract

fetched live from OpenAlex

Background: The Outcomes of Babies With Opioid Exposure (OBOE) study is an observational cohort study examining the impact of antenatal opioid exposure on outcomes from birth to 2 years of age. COVID-19 social distancing measures presented challenges to research coordinators discussing the study at length with potential participants during the birth hospitalization, which impacted recruitment, particularly among caregivers of unexposed (control) infants. In response, the OBOE study developed a digital tool (consenter video) to supplement the informed consent process, make it more engaging, and foster greater identification with the research procedures among potential participants. Objective: We aim to examine knowledge of the study, experiences with the consent process, and perceptions of the consenter video among potential participants of the OBOE study. Methods: Analyses included 129 caregivers who were given the option to view the consenter video as a supplement to the consent process. Participants selected from 3 racially and ethnically diverse avatars to guide them through the 11-minute video with recorded voice-overs. After viewing the consenter video, participants completed a short survey to assess their knowledge of the study, experiences with the consent process, and perceptions of the tool, regardless of their decision to enroll in the main study. Chi-square tests were used to assess differences between caregivers of opioid-exposed and unexposed infants in survey responses and whether caregivers who selected avatars consistent with their racial or ethnic background were more likely to enroll in the study than those who selected avatars that were not consistent with their background. Results: Participants demonstrated good understanding of the information presented, with 95% (n=123) correctly identifying the study purpose and 88% (n=112) correctly indicating that their infant would not be exposed to radiation during the magnetic resonance imaging. Nearly all indicated they were provided "just the right amount of information" (n=123, 98%) and that they understood the consent information well enough to decide whether to enroll (n=125, 97%). Survey responses were similar between caregivers of opioid-exposed infants and unexposed infants on all items except the decision to enroll. Those in the opioid-exposed group were more likely to enroll in the main study compared to the unexposed group (n=49, 89% vs n=38, 51%; P<.001). Of 81 caregivers with known race or ethnicity, 35 (43%) chose avatars to guide them through the video that matched their background. Caregivers selecting avatars consistent with their racial or ethnic background were more likely to enroll in the main study (n=29, 83% vs n=43, 57%; P=.01). Conclusions: This interactive digital tool was helpful in informing prospective participants about the study. The consenter tool enhanced the informed consent process, reinforced why caregivers of unexposed infants were being approached, and was particularly helpful as a resource for families to understand magnetic resonance imaging procedures.

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

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.066
metaresearch head score (Gemma)0.090
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.349

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0660.090
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.042
GPT teacher head0.412
Teacher spread0.370 · 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

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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