Evidence map›Paper›PMID 40472835›Full record

ArticleJournal of speech, language, and hearing research : JSLHR2025

The Use of Automated Digital Data in Speech, Language, and Hearing Research: Confronting a New Ethical Landscape.

Batya Elbaum, Lynn K Perry, Christina M Sarangoulis, Kenneth W Goodman, Daniel S Messinger, Ivette Cejas

Abstract read
In one paragraph

Article in Journal of speech, language, and hearing research : JSLHR, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

6 authors.

Batya ElbaumDepartment of Teaching and Learning, University of Miami, Coral Gables, FL.ORCID 0000-0002-1257-8251
Lynn K PerryDepartment of Psychology, University of Miami, Coral Gables, FL.ORCID 0000-0001-6976-3741
Christina M SarangoulisDepartment of Otolaryngology, University of Miami, Coral Gables, FL.
Kenneth W GoodmanInstitute for Bioethics and Health Policy, University of Miami, Coral Gables, FL.ORCID 0000-0002-0149-8432
Daniel S MessingerDepartment of Psychology, University of Miami, Coral Gables, FL.ORCID 0000-0002-9551-675X
Ivette CejasDepartment of Otolaryngology, University of Miami, Coral Gables, FL.ORCID 0000-0002-2083-9060

Funding

Language Development and Social Interaction in Children with Hearing LossR01DC018542 · NIDCD · UNIVERSITY OF MIAMI CORAL GABLES · PI MESSINGER, DANIEL S, PERRY, LYNN K · 2021 to 2025
$2.1M
NIDCD NIH HHS R01 DC018542
6 · The paper itself

Abstract

purposeThe use of automated, digital data collection, such as daylong audio recordings of children's language environments, is yielding important insights for both researchers and practitioners in the field of communication disorders. However, ethical issues involved in the use of digital tools for research purposes have yet to be thoroughly explored.

methodIn this commentary, we draw on our experience with automated data collection in inclusive auditory oral preschool classrooms, as well as interviews with parents, teachers, speech-language pathologists, researchers, and other community members, to identify key areas of ethical concern and draw out implications for future research.

conclusionWe discuss specific issues and recommendations related to three emerging areas of concern: data storage and data sharing, the return of results to research participants, and the communication of incidental findings.

Indexed as

Data CollectionSpeechChild, PreschoolEthics, ResearchHumansInformation DisseminationSpeech-Language Pathology

Identifiers

PMID40472835
PMCPMC12384941

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.